Last updated on 2024-06-09 03:52:21 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.12.0 | 158.72 | 340.07 | 498.79 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.12.0 | 112.10 | 240.92 | 353.02 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.12.0 | 654.36 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.12.0 | 655.18 | ERROR | |||
| r-devel-windows-x86_64 | 0.12.0 | 117.00 | 283.00 | 400.00 | ERROR | |
| r-patched-linux-x86_64 | 0.12.0 | 135.36 | 344.35 | 479.71 | OK | |
| r-release-linux-x86_64 | 0.12.0 | 129.54 | 348.63 | 478.17 | OK | |
| r-release-macos-arm64 | 0.12.0 | 171.00 | NOTE | |||
| r-release-macos-x86_64 | 0.12.0 | 232.00 | NOTE | |||
| r-release-windows-x86_64 | 0.12.0 | 118.00 | 303.00 | 421.00 | NOTE | |
| r-oldrel-macos-arm64 | 0.12.0 | 167.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 0.12.0 | 392.00 | NOTE | |||
| r-oldrel-windows-x86_64 | 0.12.0 | 148.00 | 356.00 | 504.00 | NOTE |
clang-UBSAN gcc-UBSAN valgrind
Version: 0.12.0
Check: tests
Result: ERROR
Running ‘fixest_tests.R’ [10s/12s]
Running the tests in ‘tests/fixest_tests.R’ failed.
Complete output:
> #----------------------------------------------#
> # Author: Laurent Berge
> # Date creation: Fri Jul 10 09:03:06 2020
> # ~: package sniff tests
> #----------------------------------------------#
>
> # Not everything is currently covered, but I'll improve it over time
>
> # Some functions are not trivial to test properly though
>
> library(fixest)
>
> test = fixest:::test ; chunk = fixest:::chunk
> vcovClust = fixest:::vcovClust
> stvec = stringmagic::string_vec_alias()
>
> setFixest_notes(FALSE)
>
> if(fixest:::is_r_check()){
+ if(requireNamespace("data.table", quietly = TRUE)){
+ library(data.table)
+ data.table::setDTthreads(1)
+ }
+ setFixest_nthreads(1)
+ }
>
> ####
> #### ESTIMATIONS ####
> ####
>
> ####
> #### ... Main ####
> ####
>
>
> chunk("ESTIMATION")
ESTIMATION
>
> set.seed(0)
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "species")
> base$fe_2 = rep(1:5, 30)
> base$fe_3 = sample(15, 150, TRUE)
> base$constant = 5
> base$y_int = as.integer(base$y)
> base$w = as.vector(unclass(base$species) - 0.95)
> base$offset_value = unclass(base$species) - 0.95
> base$y_01 = 1 * ((scale(base$x1) + rnorm(150)) > 0)
> # what follows to avoid removal of fixed-effects (logit is pain in the neck)
> base$y_01[1:5 + rep(c(0, 50, 100), each = 5)] = 1
> base$y_01[6:10 + rep(c(0, 50, 100), each = 5)] = 0
> # We enforce the removal of observations
> base$y_int_null = base$y_int
> base$y_int_null[base$fe_3 %in% 1:5] = 0
>
> for(model in c("ols", "pois", "logit", "negbin", "Gamma")){
+ cat("Model: ", format(model, width = 6), sep = "")
+ for(use_weights in c(FALSE, TRUE)){
+ my_weight = NULL
+ if(use_weights) my_weight = base$w
+
+ for(use_offset in c(FALSE, TRUE)){
+ my_offset = NULL
+ if(use_offset) my_offset = base$offset_value
+
+ for(id_fe in 0:9){
+
+ cat(".")
+
+ tol = switch(model, "negbin" = 1e-2, "logit" = 3e-5, 1e-5)
+
+ # Setting up the formula to accommodate FEs
+ if(id_fe == 0){
+ fml_fixest = fml_stats = y ~ x1
+ } else if(id_fe == 1){
+ fml_fixest = y ~ x1 | species
+ fml_stats = y ~ x1 + factor(species)
+ } else if(id_fe == 2){
+ fml_fixest = y ~ x1 | species + fe_2
+ fml_stats = y ~ x1 + factor(species) + factor(fe_2)
+ } else if(id_fe == 3){
+ # varying slope
+ fml_fixest = y ~ x1 | species[[x2]]
+ fml_stats = y ~ x1 + x2:species
+ } else if(id_fe == 4){
+ # varying slope -- 1 VS, 1 FE
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2
+ fml_stats = y ~ x1 + x2:species + factor(fe_2)
+ } else if(id_fe == 5){
+ # varying slope -- 2 VS
+ fml_fixest = y ~ x1 | species[x2]
+ fml_stats = y ~ x1 + x2:species + species
+ } else if(id_fe == 6){
+ # varying slope -- 2 VS bis
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2[[x3]]
+ fml_stats = y ~ x1 + x2:species + x3:factor(fe_2)
+ } else if(id_fe == 7){
+ # Combined clusters
+ fml_fixest = y ~ x1 + x2 | species^fe_2
+ fml_stats = y ~ x1 + x2 + paste(species, fe_2)
+ } else if(id_fe == 8){
+ fml_fixest = y ~ x1 | species[x2] + fe_2[x3] + fe_3
+ fml_stats = y ~ x1 + species + i(species, x2) + factor(fe_2) + i(fe_2, x3) + factor(fe_3)
+ } else if(id_fe == 9){
+ fml_fixest = y ~ x1 | species + fe_2[x2,x3] + fe_3
+ fml_stats = y ~ x1 + species + factor(fe_2) + i(fe_2, x2) + i(fe_2, x3) + factor(fe_3)
+ }
+
+ # ad hoc modifications of the formula
+ if(model == "logit"){
+ fml_fixest = xpd(y_01 ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_01 ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ # The estimations are OK, conv differences out of my control
+ if(id_fe %in% 8:9) tol = 0.5
+
+ } else if(model == "pois"){
+ fml_fixest = xpd(y_int_null ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int_null ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ } else if(model %in% c("negbin", "Gamma")){
+ fml_fixest = xpd(y_int ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int ~ ..rhs, ..rhs = fml_stats[[3]])
+ }
+
+ adj = 1
+ if(model == "ols"){
+ res = feols(fml_fixest, base, weights = my_weight, offset = my_offset)
+ res_bis = lm(fml_stats, base, weights = my_weight, offset = my_offset)
+
+ } else if(model %in% c("pois", "logit", "Gamma")){
+ adj = 0
+ if(model == "Gamma" && use_offset) next
+
+ my_family = switch(model, pois = poisson(), logit = binomial(), Gamma = Gamma())
+
+ res = feglm(fml_fixest, base, family = my_family, weights = my_weight, offset = my_offset)
+
+ if(!is.null(res$obs_selection$obsRemoved)){
+ qui = res$obs_selection$obsRemoved
+
+ # I MUST do that.... => subset does not work...
+ base_tmp = base[qui, ]
+ base_tmp$my_offset = my_offset[qui]
+ base_tmp$my_weight = my_weight[qui]
+ res_bis = glm(fml_stats, base_tmp, family = my_family, weights = my_weight, offset = my_offset)
+ } else {
+ res_bis = glm(fml_stats, data = base, family = my_family, weights = my_weight, offset = my_offset)
+ }
+
+ } else if(model == "negbin"){
+ # no offset in glm.nb + no VS in fenegbin + no weights in fenegbin
+ if(use_weights || use_offset || id_fe > 2) next
+
+ res = fenegbin(fml_fixest, base, notes = FALSE)
+ res_bis = MASS::glm.nb(fml_stats, base)
+
+ }
+
+ test(coef(res)["x1"], coef(res_bis)["x1"], "~", tol)
+ test(se(res, se = "st", ssc = ssc(adj = adj))["x1"], se(res_bis)["x1"], "~", tol)
+ test(pvalue(res, se = "st", ssc = ssc(adj = adj))["x1"], pvalue(res_bis)["x1"], "~", tol*10**(model == "negbin"))
+ # cat("Model: ", model, ", FE: ", id_fe, ", weight: ", use_weights, ", offset: ", use_offset, "\n", sep="")
+
+ }
+ cat("|")
+ }
+ }
+ cat("\n")
+ }
Model: ols ..........|..........|..........|..........|
Model: pois ..........|..........|..........|..........|
Model: logit ..........|..........|..........|..........|
Model: negbin..........|..........|..........|..........|
Model: Gamma ..........|..........|..........|..........|
There were 36 warnings (use warnings() to see them)
>
> ####
> #### ... Corner cases ####
> ####
>
> chunk("Corner cases")
CORNER CASES
>
>
> # We test the absence of bugs
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "fe1")
> base$fe2 = rep(1:5, 30)
> base$y[1:5] = NA
> base$x1[4:8] = NA
> base$x2[4:21] = NA
> base$x3[110:111] = NA
> base$fe1[110:118] = NA
> base$fe2[base$fe2 == 1] = 0
> base$fe3 = sample(letters[1:5], 150, TRUE)
> base$period = rep(1:50, 3)
> base$x_cst = 1
>
> res = feols(y ~ 1 | csw(fe1, fe1^fe2), base)
>
> res = feols(y ~ 1 + csw(x1, i(fe1)) | fe2, base)
>
> res = feols(y ~ csw(f(x1, 1:2), x2) | sw0(fe2, fe2^fe3), base, panel.id = ~ fe1 + period)
>
> res = feols(d(y) ~ -1 + d(x2), base, panel.id = ~ fe1 + period)
> test(length(coef(res)), 1)
>
> res = feols(c(y, x1) ~ 1 | fe1 | x2 ~ x3, base)
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: cpp_iv_products(X = X_demean, y = y_demean, Z = iv.mat_demean, u = iv_lhs_demean, w = weights, nthreads = nthreads)
2: feols(c(y, x1) ~ 1 | fe1 | x2 ~ x3, base)
An irrecoverable exception occurred. R is aborting now ...
Segmentation fault
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.12.0
Check: tests
Result: ERROR
Running ‘fixest_tests.R’ [7s/10s]
Running the tests in ‘tests/fixest_tests.R’ failed.
Complete output:
> #----------------------------------------------#
> # Author: Laurent Berge
> # Date creation: Fri Jul 10 09:03:06 2020
> # ~: package sniff tests
> #----------------------------------------------#
>
> # Not everything is currently covered, but I'll improve it over time
>
> # Some functions are not trivial to test properly though
>
> library(fixest)
>
> test = fixest:::test ; chunk = fixest:::chunk
> vcovClust = fixest:::vcovClust
> stvec = stringmagic::string_vec_alias()
>
> setFixest_notes(FALSE)
>
> if(fixest:::is_r_check()){
+ if(requireNamespace("data.table", quietly = TRUE)){
+ library(data.table)
+ data.table::setDTthreads(1)
+ }
+ setFixest_nthreads(1)
+ }
>
> ####
> #### ESTIMATIONS ####
> ####
>
> ####
> #### ... Main ####
> ####
>
>
> chunk("ESTIMATION")
ESTIMATION
>
> set.seed(0)
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "species")
> base$fe_2 = rep(1:5, 30)
> base$fe_3 = sample(15, 150, TRUE)
> base$constant = 5
> base$y_int = as.integer(base$y)
> base$w = as.vector(unclass(base$species) - 0.95)
> base$offset_value = unclass(base$species) - 0.95
> base$y_01 = 1 * ((scale(base$x1) + rnorm(150)) > 0)
> # what follows to avoid removal of fixed-effects (logit is pain in the neck)
> base$y_01[1:5 + rep(c(0, 50, 100), each = 5)] = 1
> base$y_01[6:10 + rep(c(0, 50, 100), each = 5)] = 0
> # We enforce the removal of observations
> base$y_int_null = base$y_int
> base$y_int_null[base$fe_3 %in% 1:5] = 0
>
> for(model in c("ols", "pois", "logit", "negbin", "Gamma")){
+ cat("Model: ", format(model, width = 6), sep = "")
+ for(use_weights in c(FALSE, TRUE)){
+ my_weight = NULL
+ if(use_weights) my_weight = base$w
+
+ for(use_offset in c(FALSE, TRUE)){
+ my_offset = NULL
+ if(use_offset) my_offset = base$offset_value
+
+ for(id_fe in 0:9){
+
+ cat(".")
+
+ tol = switch(model, "negbin" = 1e-2, "logit" = 3e-5, 1e-5)
+
+ # Setting up the formula to accommodate FEs
+ if(id_fe == 0){
+ fml_fixest = fml_stats = y ~ x1
+ } else if(id_fe == 1){
+ fml_fixest = y ~ x1 | species
+ fml_stats = y ~ x1 + factor(species)
+ } else if(id_fe == 2){
+ fml_fixest = y ~ x1 | species + fe_2
+ fml_stats = y ~ x1 + factor(species) + factor(fe_2)
+ } else if(id_fe == 3){
+ # varying slope
+ fml_fixest = y ~ x1 | species[[x2]]
+ fml_stats = y ~ x1 + x2:species
+ } else if(id_fe == 4){
+ # varying slope -- 1 VS, 1 FE
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2
+ fml_stats = y ~ x1 + x2:species + factor(fe_2)
+ } else if(id_fe == 5){
+ # varying slope -- 2 VS
+ fml_fixest = y ~ x1 | species[x2]
+ fml_stats = y ~ x1 + x2:species + species
+ } else if(id_fe == 6){
+ # varying slope -- 2 VS bis
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2[[x3]]
+ fml_stats = y ~ x1 + x2:species + x3:factor(fe_2)
+ } else if(id_fe == 7){
+ # Combined clusters
+ fml_fixest = y ~ x1 + x2 | species^fe_2
+ fml_stats = y ~ x1 + x2 + paste(species, fe_2)
+ } else if(id_fe == 8){
+ fml_fixest = y ~ x1 | species[x2] + fe_2[x3] + fe_3
+ fml_stats = y ~ x1 + species + i(species, x2) + factor(fe_2) + i(fe_2, x3) + factor(fe_3)
+ } else if(id_fe == 9){
+ fml_fixest = y ~ x1 | species + fe_2[x2,x3] + fe_3
+ fml_stats = y ~ x1 + species + factor(fe_2) + i(fe_2, x2) + i(fe_2, x3) + factor(fe_3)
+ }
+
+ # ad hoc modifications of the formula
+ if(model == "logit"){
+ fml_fixest = xpd(y_01 ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_01 ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ # The estimations are OK, conv differences out of my control
+ if(id_fe %in% 8:9) tol = 0.5
+
+ } else if(model == "pois"){
+ fml_fixest = xpd(y_int_null ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int_null ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ } else if(model %in% c("negbin", "Gamma")){
+ fml_fixest = xpd(y_int ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int ~ ..rhs, ..rhs = fml_stats[[3]])
+ }
+
+ adj = 1
+ if(model == "ols"){
+ res = feols(fml_fixest, base, weights = my_weight, offset = my_offset)
+ res_bis = lm(fml_stats, base, weights = my_weight, offset = my_offset)
+
+ } else if(model %in% c("pois", "logit", "Gamma")){
+ adj = 0
+ if(model == "Gamma" && use_offset) next
+
+ my_family = switch(model, pois = poisson(), logit = binomial(), Gamma = Gamma())
+
+ res = feglm(fml_fixest, base, family = my_family, weights = my_weight, offset = my_offset)
+
+ if(!is.null(res$obs_selection$obsRemoved)){
+ qui = res$obs_selection$obsRemoved
+
+ # I MUST do that.... => subset does not work...
+ base_tmp = base[qui, ]
+ base_tmp$my_offset = my_offset[qui]
+ base_tmp$my_weight = my_weight[qui]
+ res_bis = glm(fml_stats, base_tmp, family = my_family, weights = my_weight, offset = my_offset)
+ } else {
+ res_bis = glm(fml_stats, data = base, family = my_family, weights = my_weight, offset = my_offset)
+ }
+
+ } else if(model == "negbin"){
+ # no offset in glm.nb + no VS in fenegbin + no weights in fenegbin
+ if(use_weights || use_offset || id_fe > 2) next
+
+ res = fenegbin(fml_fixest, base, notes = FALSE)
+ res_bis = MASS::glm.nb(fml_stats, base)
+
+ }
+
+ test(coef(res)["x1"], coef(res_bis)["x1"], "~", tol)
+ test(se(res, se = "st", ssc = ssc(adj = adj))["x1"], se(res_bis)["x1"], "~", tol)
+ test(pvalue(res, se = "st", ssc = ssc(adj = adj))["x1"], pvalue(res_bis)["x1"], "~", tol*10**(model == "negbin"))
+ # cat("Model: ", model, ", FE: ", id_fe, ", weight: ", use_weights, ", offset: ", use_offset, "\n", sep="")
+
+ }
+ cat("|")
+ }
+ }
+ cat("\n")
+ }
Model: ols ..........|..........|..........|..........|
Model: pois ..........|..........|..........|..........|
Model: logit ..........|..........|..........|..........|
Model: negbin..........|..........|..........|..........|
Model: Gamma ..........|..........|..........|..........|
There were 36 warnings (use warnings() to see them)
>
> ####
> #### ... Corner cases ####
> ####
>
> chunk("Corner cases")
CORNER CASES
>
>
> # We test the absence of bugs
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "fe1")
> base$fe2 = rep(1:5, 30)
> base$y[1:5] = NA
> base$x1[4:8] = NA
> base$x2[4:21] = NA
> base$x3[110:111] = NA
> base$fe1[110:118] = NA
> base$fe2[base$fe2 == 1] = 0
> base$fe3 = sample(letters[1:5], 150, TRUE)
> base$period = rep(1:50, 3)
> base$x_cst = 1
>
> res = feols(y ~ 1 | csw(fe1, fe1^fe2), base)
>
> res = feols(y ~ 1 + csw(x1, i(fe1)) | fe2, base)
>
> res = feols(y ~ csw(f(x1, 1:2), x2) | sw0(fe2, fe2^fe3), base, panel.id = ~ fe1 + period)
>
> res = feols(d(y) ~ -1 + d(x2), base, panel.id = ~ fe1 + period)
> test(length(coef(res)), 1)
>
> res = feols(c(y, x1) ~ 1 | fe1 | x2 ~ x3, base)
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: cpp_iv_products(X = X_demean, y = y_demean, Z = iv.mat_demean, u = iv_lhs_demean, w = weights, nthreads = nthreads)
2: feols(c(y, x1) ~ 1 | fe1 | x2 ~ x3, base)
An irrecoverable exception occurred. R is aborting now ...
Segmentation fault
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.12.0
Check: installed package size
Result: NOTE
installed size is 6.9Mb
sub-directories of 1Mb or more:
R 1.4Mb
doc 3.6Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-windows-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 0.12.0
Check: tests
Result: ERROR
Running ‘fixest_tests.R’ [13s/15s]
Running the tests in ‘tests/fixest_tests.R’ failed.
Complete output:
> #----------------------------------------------#
> # Author: Laurent Berge
> # Date creation: Fri Jul 10 09:03:06 2020
> # ~: package sniff tests
> #----------------------------------------------#
>
> # Not everything is currently covered, but I'll improve it over time
>
> # Some functions are not trivial to test properly though
>
> library(fixest)
>
> test = fixest:::test ; chunk = fixest:::chunk
> vcovClust = fixest:::vcovClust
> stvec = stringmagic::string_vec_alias()
>
> setFixest_notes(FALSE)
>
> if(fixest:::is_r_check()){
+ if(requireNamespace("data.table", quietly = TRUE)){
+ library(data.table)
+ data.table::setDTthreads(1)
+ }
+ setFixest_nthreads(1)
+ }
>
> ####
> #### ESTIMATIONS ####
> ####
>
> ####
> #### ... Main ####
> ####
>
>
> chunk("ESTIMATION")
ESTIMATION
>
> set.seed(0)
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "species")
> base$fe_2 = rep(1:5, 30)
> base$fe_3 = sample(15, 150, TRUE)
> base$constant = 5
> base$y_int = as.integer(base$y)
> base$w = as.vector(unclass(base$species) - 0.95)
> base$offset_value = unclass(base$species) - 0.95
> base$y_01 = 1 * ((scale(base$x1) + rnorm(150)) > 0)
> # what follows to avoid removal of fixed-effects (logit is pain in the neck)
> base$y_01[1:5 + rep(c(0, 50, 100), each = 5)] = 1
> base$y_01[6:10 + rep(c(0, 50, 100), each = 5)] = 0
> # We enforce the removal of observations
> base$y_int_null = base$y_int
> base$y_int_null[base$fe_3 %in% 1:5] = 0
>
> for(model in c("ols", "pois", "logit", "negbin", "Gamma")){
+ cat("Model: ", format(model, width = 6), sep = "")
+ for(use_weights in c(FALSE, TRUE)){
+ my_weight = NULL
+ if(use_weights) my_weight = base$w
+
+ for(use_offset in c(FALSE, TRUE)){
+ my_offset = NULL
+ if(use_offset) my_offset = base$offset_value
+
+ for(id_fe in 0:9){
+
+ cat(".")
+
+ tol = switch(model, "negbin" = 1e-2, "logit" = 3e-5, 1e-5)
+
+ # Setting up the formula to accommodate FEs
+ if(id_fe == 0){
+ fml_fixest = fml_stats = y ~ x1
+ } else if(id_fe == 1){
+ fml_fixest = y ~ x1 | species
+ fml_stats = y ~ x1 + factor(species)
+ } else if(id_fe == 2){
+ fml_fixest = y ~ x1 | species + fe_2
+ fml_stats = y ~ x1 + factor(species) + factor(fe_2)
+ } else if(id_fe == 3){
+ # varying slope
+ fml_fixest = y ~ x1 | species[[x2]]
+ fml_stats = y ~ x1 + x2:species
+ } else if(id_fe == 4){
+ # varying slope -- 1 VS, 1 FE
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2
+ fml_stats = y ~ x1 + x2:species + factor(fe_2)
+ } else if(id_fe == 5){
+ # varying slope -- 2 VS
+ fml_fixest = y ~ x1 | species[x2]
+ fml_stats = y ~ x1 + x2:species + species
+ } else if(id_fe == 6){
+ # varying slope -- 2 VS bis
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2[[x3]]
+ fml_stats = y ~ x1 + x2:species + x3:factor(fe_2)
+ } else if(id_fe == 7){
+ # Combined clusters
+ fml_fixest = y ~ x1 + x2 | species^fe_2
+ fml_stats = y ~ x1 + x2 + paste(species, fe_2)
+ } else if(id_fe == 8){
+ fml_fixest = y ~ x1 | species[x2] + fe_2[x3] + fe_3
+ fml_stats = y ~ x1 + species + i(species, x2) + factor(fe_2) + i(fe_2, x3) + factor(fe_3)
+ } else if(id_fe == 9){
+ fml_fixest = y ~ x1 | species + fe_2[x2,x3] + fe_3
+ fml_stats = y ~ x1 + species + factor(fe_2) + i(fe_2, x2) + i(fe_2, x3) + factor(fe_3)
+ }
+
+ # ad hoc modifications of the formula
+ if(model == "logit"){
+ fml_fixest = xpd(y_01 ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_01 ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ # The estimations are OK, conv differences out of my control
+ if(id_fe %in% 8:9) tol = 0.5
+
+ } else if(model == "pois"){
+ fml_fixest = xpd(y_int_null ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int_null ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ } else if(model %in% c("negbin", "Gamma")){
+ fml_fixest = xpd(y_int ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int ~ ..rhs, ..rhs = fml_stats[[3]])
+ }
+
+ adj = 1
+ if(model == "ols"){
+ res = feols(fml_fixest, base, weights = my_weight, offset = my_offset)
+ res_bis = lm(fml_stats, base, weights = my_weight, offset = my_offset)
+
+ } else if(model %in% c("pois", "logit", "Gamma")){
+ adj = 0
+ if(model == "Gamma" && use_offset) next
+
+ my_family = switch(model, pois = poisson(), logit = binomial(), Gamma = Gamma())
+
+ res = feglm(fml_fixest, base, family = my_family, weights = my_weight, offset = my_offset)
+
+ if(!is.null(res$obs_selection$obsRemoved)){
+ qui = res$obs_selection$obsRemoved
+
+ # I MUST do that.... => subset does not work...
+ base_tmp = base[qui, ]
+ base_tmp$my_offset = my_offset[qui]
+ base_tmp$my_weight = my_weight[qui]
+ res_bis = glm(fml_stats, base_tmp, family = my_family, weights = my_weight, offset = my_offset)
+ } else {
+ res_bis = glm(fml_stats, data = base, family = my_family, weights = my_weight, offset = my_offset)
+ }
+
+ } else if(model == "negbin"){
+ # no offset in glm.nb + no VS in fenegbin + no weights in fenegbin
+ if(use_weights || use_offset || id_fe > 2) next
+
+ res = fenegbin(fml_fixest, base, notes = FALSE)
+ res_bis = MASS::glm.nb(fml_stats, base)
+
+ }
+
+ test(coef(res)["x1"], coef(res_bis)["x1"], "~", tol)
+ test(se(res, se = "st", ssc = ssc(adj = adj))["x1"], se(res_bis)["x1"], "~", tol)
+ test(pvalue(res, se = "st", ssc = ssc(adj = adj))["x1"], pvalue(res_bis)["x1"], "~", tol*10**(model == "negbin"))
+ # cat("Model: ", model, ", FE: ", id_fe, ", weight: ", use_weights, ", offset: ", use_offset, "\n", sep="")
+
+ }
+ cat("|")
+ }
+ }
+ cat("\n")
+ }
Model: ols ..........|..........|..........|..........|
Model: pois ..........|..........|..........|..........|
Model: logit ..........|..........|..........|..........|
Model: negbin..........|..........|..........|..........|
Model: Gamma ..........|..........|..........|..........|
There were 36 warnings (use warnings() to see them)
>
> ####
> #### ... Corner cases ####
> ####
>
> chunk("Corner cases")
CORNER CASES
>
>
> # We test the absence of bugs
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "fe1")
> base$fe2 = rep(1:5, 30)
> base$y[1:5] = NA
> base$x1[4:8] = NA
> base$x2[4:21] = NA
> base$x3[110:111] = NA
> base$fe1[110:118] = NA
> base$fe2[base$fe2 == 1] = 0
> base$fe3 = sample(letters[1:5], 150, TRUE)
> base$period = rep(1:50, 3)
> base$x_cst = 1
>
> res = feols(y ~ 1 | csw(fe1, fe1^fe2), base)
>
> res = feols(y ~ 1 + csw(x1, i(fe1)) | fe2, base)
>
> res = feols(y ~ csw(f(x1, 1:2), x2) | sw0(fe2, fe2^fe3), base, panel.id = ~ fe1 + period)
>
> res = feols(d(y) ~ -1 + d(x2), base, panel.id = ~ fe1 + period)
> test(length(coef(res)), 1)
>
> res = feols(c(y, x1) ~ 1 | fe1 | x2 ~ x3, base)
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: cpp_iv_products(X = X_demean, y = y_demean, Z = iv.mat_demean, u = iv_lhs_demean, w = weights, nthreads = nthreads)
2: feols(c(y, x1) ~ 1 | fe1 | x2 ~ x3, base)
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.12.0
Check: tests
Result: ERROR
Running ‘fixest_tests.R’ [14s/21s]
Running the tests in ‘tests/fixest_tests.R’ failed.
Complete output:
> #----------------------------------------------#
> # Author: Laurent Berge
> # Date creation: Fri Jul 10 09:03:06 2020
> # ~: package sniff tests
> #----------------------------------------------#
>
> # Not everything is currently covered, but I'll improve it over time
>
> # Some functions are not trivial to test properly though
>
> library(fixest)
>
> test = fixest:::test ; chunk = fixest:::chunk
> vcovClust = fixest:::vcovClust
> stvec = stringmagic::string_vec_alias()
>
> setFixest_notes(FALSE)
>
> if(fixest:::is_r_check()){
+ if(requireNamespace("data.table", quietly = TRUE)){
+ library(data.table)
+ data.table::setDTthreads(1)
+ }
+ setFixest_nthreads(1)
+ }
>
> ####
> #### ESTIMATIONS ####
> ####
>
> ####
> #### ... Main ####
> ####
>
>
> chunk("ESTIMATION")
ESTIMATION
>
> set.seed(0)
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "species")
> base$fe_2 = rep(1:5, 30)
> base$fe_3 = sample(15, 150, TRUE)
> base$constant = 5
> base$y_int = as.integer(base$y)
> base$w = as.vector(unclass(base$species) - 0.95)
> base$offset_value = unclass(base$species) - 0.95
> base$y_01 = 1 * ((scale(base$x1) + rnorm(150)) > 0)
> # what follows to avoid removal of fixed-effects (logit is pain in the neck)
> base$y_01[1:5 + rep(c(0, 50, 100), each = 5)] = 1
> base$y_01[6:10 + rep(c(0, 50, 100), each = 5)] = 0
> # We enforce the removal of observations
> base$y_int_null = base$y_int
> base$y_int_null[base$fe_3 %in% 1:5] = 0
>
> for(model in c("ols", "pois", "logit", "negbin", "Gamma")){
+ cat("Model: ", format(model, width = 6), sep = "")
+ for(use_weights in c(FALSE, TRUE)){
+ my_weight = NULL
+ if(use_weights) my_weight = base$w
+
+ for(use_offset in c(FALSE, TRUE)){
+ my_offset = NULL
+ if(use_offset) my_offset = base$offset_value
+
+ for(id_fe in 0:9){
+
+ cat(".")
+
+ tol = switch(model, "negbin" = 1e-2, "logit" = 3e-5, 1e-5)
+
+ # Setting up the formula to accommodate FEs
+ if(id_fe == 0){
+ fml_fixest = fml_stats = y ~ x1
+ } else if(id_fe == 1){
+ fml_fixest = y ~ x1 | species
+ fml_stats = y ~ x1 + factor(species)
+ } else if(id_fe == 2){
+ fml_fixest = y ~ x1 | species + fe_2
+ fml_stats = y ~ x1 + factor(species) + factor(fe_2)
+ } else if(id_fe == 3){
+ # varying slope
+ fml_fixest = y ~ x1 | species[[x2]]
+ fml_stats = y ~ x1 + x2:species
+ } else if(id_fe == 4){
+ # varying slope -- 1 VS, 1 FE
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2
+ fml_stats = y ~ x1 + x2:species + factor(fe_2)
+ } else if(id_fe == 5){
+ # varying slope -- 2 VS
+ fml_fixest = y ~ x1 | species[x2]
+ fml_stats = y ~ x1 + x2:species + species
+ } else if(id_fe == 6){
+ # varying slope -- 2 VS bis
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2[[x3]]
+ fml_stats = y ~ x1 + x2:species + x3:factor(fe_2)
+ } else if(id_fe == 7){
+ # Combined clusters
+ fml_fixest = y ~ x1 + x2 | species^fe_2
+ fml_stats = y ~ x1 + x2 + paste(species, fe_2)
+ } else if(id_fe == 8){
+ fml_fixest = y ~ x1 | species[x2] + fe_2[x3] + fe_3
+ fml_stats = y ~ x1 + species + i(species, x2) + factor(fe_2) + i(fe_2, x3) + factor(fe_3)
+ } else if(id_fe == 9){
+ fml_fixest = y ~ x1 | species + fe_2[x2,x3] + fe_3
+ fml_stats = y ~ x1 + species + factor(fe_2) + i(fe_2, x2) + i(fe_2, x3) + factor(fe_3)
+ }
+
+ # ad hoc modifications of the formula
+ if(model == "logit"){
+ fml_fixest = xpd(y_01 ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_01 ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ # The estimations are OK, conv differences out of my control
+ if(id_fe %in% 8:9) tol = 0.5
+
+ } else if(model == "pois"){
+ fml_fixest = xpd(y_int_null ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int_null ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ } else if(model %in% c("negbin", "Gamma")){
+ fml_fixest = xpd(y_int ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int ~ ..rhs, ..rhs = fml_stats[[3]])
+ }
+
+ adj = 1
+ if(model == "ols"){
+ res = feols(fml_fixest, base, weights = my_weight, offset = my_offset)
+ res_bis = lm(fml_stats, base, weights = my_weight, offset = my_offset)
+
+ } else if(model %in% c("pois", "logit", "Gamma")){
+ adj = 0
+ if(model == "Gamma" && use_offset) next
+
+ my_family = switch(model, pois = poisson(), logit = binomial(), Gamma = Gamma())
+
+ res = feglm(fml_fixest, base, family = my_family, weights = my_weight, offset = my_offset)
+
+ if(!is.null(res$obs_selection$obsRemoved)){
+ qui = res$obs_selection$obsRemoved
+
+ # I MUST do that.... => subset does not work...
+ base_tmp = base[qui, ]
+ base_tmp$my_offset = my_offset[qui]
+ base_tmp$my_weight = my_weight[qui]
+ res_bis = glm(fml_stats, base_tmp, family = my_family, weights = my_weight, offset = my_offset)
+ } else {
+ res_bis = glm(fml_stats, data = base, family = my_family, weights = my_weight, offset = my_offset)
+ }
+
+ } else if(model == "negbin"){
+ # no offset in glm.nb + no VS in fenegbin + no weights in fenegbin
+ if(use_weights || use_offset || id_fe > 2) next
+
+ res = fenegbin(fml_fixest, base, notes = FALSE)
+ res_bis = MASS::glm.nb(fml_stats, base)
+
+ }
+
+ test(coef(res)["x1"], coef(res_bis)["x1"], "~", tol)
+ test(se(res, se = "st", ssc = ssc(adj = adj))["x1"], se(res_bis)["x1"], "~", tol)
+ test(pvalue(res, se = "st", ssc = ssc(adj = adj))["x1"], pvalue(res_bis)["x1"], "~", tol*10**(model == "negbin"))
+ # cat("Model: ", model, ", FE: ", id_fe, ", weight: ", use_weights, ", offset: ", use_offset, "\n", sep="")
+
+ }
+ cat("|")
+ }
+ }
+ cat("\n")
+ }
Model: ols ..........|..........|..........|..........|
Model: pois ..........|..........|..........|..........|
Model: logit ..........|..........|..........|..........|
Model: negbin..........|..........|..........|..........|
Model: Gamma ..........|..........|..........|..........|
There were 36 warnings (use warnings() to see them)
>
> ####
> #### ... Corner cases ####
> ####
>
> chunk("Corner cases")
CORNER CASES
>
>
> # We test the absence of bugs
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "fe1")
> base$fe2 = rep(1:5, 30)
> base$y[1:5] = NA
> base$x1[4:8] = NA
> base$x2[4:21] = NA
> base$x3[110:111] = NA
> base$fe1[110:118] = NA
> base$fe2[base$fe2 == 1] = 0
> base$fe3 = sample(letters[1:5], 150, TRUE)
> base$period = rep(1:50, 3)
> base$x_cst = 1
>
> res = feols(y ~ 1 | csw(fe1, fe1^fe2), base)
>
> res = feols(y ~ 1 + csw(x1, i(fe1)) | fe2, base)
>
> res = feols(y ~ csw(f(x1, 1:2), x2) | sw0(fe2, fe2^fe3), base, panel.id = ~ fe1 + period)
>
> res = feols(d(y) ~ -1 + d(x2), base, panel.id = ~ fe1 + period)
> test(length(coef(res)), 1)
>
> res = feols(c(y, x1) ~ 1 | fe1 | x2 ~ x3, base)
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: cpp_iv_products(X = X_demean, y = y_demean, Z = iv.mat_demean, u = iv_lhs_demean, w = weights, nthreads = nthreads)
2: feols(c(y, x1) ~ 1 | fe1 | x2 ~ x3, base)
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.12.0
Check: tests
Result: ERROR
Running 'fixest_tests.R' [7s]
Running the tests in 'tests/fixest_tests.R' failed.
Complete output:
> #----------------------------------------------#
> # Author: Laurent Berge
> # Date creation: Fri Jul 10 09:03:06 2020
> # ~: package sniff tests
> #----------------------------------------------#
>
> # Not everything is currently covered, but I'll improve it over time
>
> # Some functions are not trivial to test properly though
>
> library(fixest)
>
> test = fixest:::test ; chunk = fixest:::chunk
> vcovClust = fixest:::vcovClust
> stvec = stringmagic::string_vec_alias()
>
> setFixest_notes(FALSE)
>
> if(fixest:::is_r_check()){
+ if(requireNamespace("data.table", quietly = TRUE)){
+ library(data.table)
+ data.table::setDTthreads(1)
+ }
+ setFixest_nthreads(1)
+ }
>
> ####
> #### ESTIMATIONS ####
> ####
>
> ####
> #### ... Main ####
> ####
>
>
> chunk("ESTIMATION")
ESTIMATION
>
> set.seed(0)
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "species")
> base$fe_2 = rep(1:5, 30)
> base$fe_3 = sample(15, 150, TRUE)
> base$constant = 5
> base$y_int = as.integer(base$y)
> base$w = as.vector(unclass(base$species) - 0.95)
> base$offset_value = unclass(base$species) - 0.95
> base$y_01 = 1 * ((scale(base$x1) + rnorm(150)) > 0)
> # what follows to avoid removal of fixed-effects (logit is pain in the neck)
> base$y_01[1:5 + rep(c(0, 50, 100), each = 5)] = 1
> base$y_01[6:10 + rep(c(0, 50, 100), each = 5)] = 0
> # We enforce the removal of observations
> base$y_int_null = base$y_int
> base$y_int_null[base$fe_3 %in% 1:5] = 0
>
> for(model in c("ols", "pois", "logit", "negbin", "Gamma")){
+ cat("Model: ", format(model, width = 6), sep = "")
+ for(use_weights in c(FALSE, TRUE)){
+ my_weight = NULL
+ if(use_weights) my_weight = base$w
+
+ for(use_offset in c(FALSE, TRUE)){
+ my_offset = NULL
+ if(use_offset) my_offset = base$offset_value
+
+ for(id_fe in 0:9){
+
+ cat(".")
+
+ tol = switch(model, "negbin" = 1e-2, "logit" = 3e-5, 1e-5)
+
+ # Setting up the formula to accommodate FEs
+ if(id_fe == 0){
+ fml_fixest = fml_stats = y ~ x1
+ } else if(id_fe == 1){
+ fml_fixest = y ~ x1 | species
+ fml_stats = y ~ x1 + factor(species)
+ } else if(id_fe == 2){
+ fml_fixest = y ~ x1 | species + fe_2
+ fml_stats = y ~ x1 + factor(species) + factor(fe_2)
+ } else if(id_fe == 3){
+ # varying slope
+ fml_fixest = y ~ x1 | species[[x2]]
+ fml_stats = y ~ x1 + x2:species
+ } else if(id_fe == 4){
+ # varying slope -- 1 VS, 1 FE
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2
+ fml_stats = y ~ x1 + x2:species + factor(fe_2)
+ } else if(id_fe == 5){
+ # varying slope -- 2 VS
+ fml_fixest = y ~ x1 | species[x2]
+ fml_stats = y ~ x1 + x2:species + species
+ } else if(id_fe == 6){
+ # varying slope -- 2 VS bis
+ fml_fixest = y ~ x1 | species[[x2]] + fe_2[[x3]]
+ fml_stats = y ~ x1 + x2:species + x3:factor(fe_2)
+ } else if(id_fe == 7){
+ # Combined clusters
+ fml_fixest = y ~ x1 + x2 | species^fe_2
+ fml_stats = y ~ x1 + x2 + paste(species, fe_2)
+ } else if(id_fe == 8){
+ fml_fixest = y ~ x1 | species[x2] + fe_2[x3] + fe_3
+ fml_stats = y ~ x1 + species + i(species, x2) + factor(fe_2) + i(fe_2, x3) + factor(fe_3)
+ } else if(id_fe == 9){
+ fml_fixest = y ~ x1 | species + fe_2[x2,x3] + fe_3
+ fml_stats = y ~ x1 + species + factor(fe_2) + i(fe_2, x2) + i(fe_2, x3) + factor(fe_3)
+ }
+
+ # ad hoc modifications of the formula
+ if(model == "logit"){
+ fml_fixest = xpd(y_01 ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_01 ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ # The estimations are OK, conv differences out of my control
+ if(id_fe %in% 8:9) tol = 0.5
+
+ } else if(model == "pois"){
+ fml_fixest = xpd(y_int_null ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int_null ~ ..rhs, ..rhs = fml_stats[[3]])
+
+ } else if(model %in% c("negbin", "Gamma")){
+ fml_fixest = xpd(y_int ~ ..rhs, ..rhs = fml_fixest[[3]])
+ fml_stats = xpd(y_int ~ ..rhs, ..rhs = fml_stats[[3]])
+ }
+
+ adj = 1
+ if(model == "ols"){
+ res = feols(fml_fixest, base, weights = my_weight, offset = my_offset)
+ res_bis = lm(fml_stats, base, weights = my_weight, offset = my_offset)
+
+ } else if(model %in% c("pois", "logit", "Gamma")){
+ adj = 0
+ if(model == "Gamma" && use_offset) next
+
+ my_family = switch(model, pois = poisson(), logit = binomial(), Gamma = Gamma())
+
+ res = feglm(fml_fixest, base, family = my_family, weights = my_weight, offset = my_offset)
+
+ if(!is.null(res$obs_selection$obsRemoved)){
+ qui = res$obs_selection$obsRemoved
+
+ # I MUST do that.... => subset does not work...
+ base_tmp = base[qui, ]
+ base_tmp$my_offset = my_offset[qui]
+ base_tmp$my_weight = my_weight[qui]
+ res_bis = glm(fml_stats, base_tmp, family = my_family, weights = my_weight, offset = my_offset)
+ } else {
+ res_bis = glm(fml_stats, data = base, family = my_family, weights = my_weight, offset = my_offset)
+ }
+
+ } else if(model == "negbin"){
+ # no offset in glm.nb + no VS in fenegbin + no weights in fenegbin
+ if(use_weights || use_offset || id_fe > 2) next
+
+ res = fenegbin(fml_fixest, base, notes = FALSE)
+ res_bis = MASS::glm.nb(fml_stats, base)
+
+ }
+
+ test(coef(res)["x1"], coef(res_bis)["x1"], "~", tol)
+ test(se(res, se = "st", ssc = ssc(adj = adj))["x1"], se(res_bis)["x1"], "~", tol)
+ test(pvalue(res, se = "st", ssc = ssc(adj = adj))["x1"], pvalue(res_bis)["x1"], "~", tol*10**(model == "negbin"))
+ # cat("Model: ", model, ", FE: ", id_fe, ", weight: ", use_weights, ", offset: ", use_offset, "\n", sep="")
+
+ }
+ cat("|")
+ }
+ }
+ cat("\n")
+ }
Model: ols ..........|..........|..........|..........|
Model: pois ..........|..........|..........|..........|
Model: logit ..........|..........|..........|..........|
Model: negbin..........|..........|..........|..........|
Model: Gamma ..........|..........|..........|..........|
There were 36 warnings (use warnings() to see them)
>
> ####
> #### ... Corner cases ####
> ####
>
> chunk("Corner cases")
CORNER CASES
>
>
> # We test the absence of bugs
>
> base = iris
> names(base) = c("y", "x1", "x2", "x3", "fe1")
> base$fe2 = rep(1:5, 30)
> base$y[1:5] = NA
> base$x1[4:8] = NA
> base$x2[4:21] = NA
> base$x3[110:111] = NA
> base$fe1[110:118] = NA
> base$fe2[base$fe2 == 1] = 0
> base$fe3 = sample(letters[1:5], 150, TRUE)
> base$period = rep(1:50, 3)
> base$x_cst = 1
>
> res = feols(y ~ 1 | csw(fe1, fe1^fe2), base)
>
> res = feols(y ~ 1 + csw(x1, i(fe1)) | fe2, base)
>
> res = feols(y ~ csw(f(x1, 1:2), x2) | sw0(fe2, fe2^fe3), base, panel.id = ~ fe1 + period)
>
> res = feols(d(y) ~ -1 + d(x2), base, panel.id = ~ fe1 + period)
> test(length(coef(res)), 1)
>
> res = feols(c(y, x1) ~ 1 | fe1 | x2 ~ x3, base)
Flavor: r-devel-windows-x86_64