[R-sig-Geo] Error in splm random effects ML model
Roger Bivand
Roger@B|v@nd @end|ng |rom nhh@no
Thu Feb 16 09:49:39 CET 2023
On Wed, 15 Feb 2023, Denys Dukhovnov wrote:
> Dear Roger,
>
> Yes, I am running R version 4.2.2 and Windows 10 OS x64, packages used
> updated to the latest version on CRAN. The panel data I am using is
> complete for all the variables and spatial weights, which made me wonder
> why the "within" specification runs perfectly fine, while the "random"
> one breaks down.
>
> Here is the error traceback:
>
>
> 11: .C64("aplsb1", SIGNATURE = c(SS$signature, SS$signature, "double",
> SS$signature, SS$signature, "double", "double", SS$signature,
> SS$signature, "double", SS$signature, SS$signature, SS$signature,
> SS$signature), nrow, ncol, A using entries, A using colindices, A using rowpointers,
> s, B using entries, B using colindices, B using rowpointers, entries = vector_dc("double",
> nzmax), colindices = vector_dc(SS$type, nzmax), rowpointers = vector_dc(SS$type,
> nrow + 1), nzmax + 1, ierr = vector_dc(SS$type, 1), INTENT = c("r",
> "r", "r", "r", "r", "r", "r", "r", "r", "w", "w", "w",
> "r", "w"), NAOK = getOption("spam.NAOK"), PACKAGE = SS$package)
> 10: spam_add(e1, e2, -1)
> 9: I - lambda * csrw
> 8: I - lambda * csrw
> 7: xprodB(lambda, w)
This is where the problem lies:
library(spam)
csrw <- as.spam(wgts)
n <- nrow(wgts)
I <- diag.spam(1, n, n)
lambda <- 0
B <- I - lambda * csrw
is OK. If lambda is NaN:
lambda <- NaN
B <- I - lambda * csrw
Error in .C64("aplsb1", SIGNATURE = c(SS$signature, SS$signature,
"double", :
NAs in argument 7 and 'NAOK = FALSE' (dotCall64)
If lambda is Inf:
lambda <- Inf
B <- I - lambda * csrw
Error in .C64("aplsb1", SIGNATURE = c(SS$signature, SS$signature,
"double", :
NAs in argument 7 and 'NAOK = FALSE' (dotCall64)
and so on. The default method="nlminb" can be changed to "BFGS":
> system.time(reg.splm.random <- spml(formula = mx.standard ~ I.score,
data = analysis.subset, listw = listw.wgts, effect = "individual", model =
"random", lag = FALSE, spatial.error = "b", index = c("Group", "Year"),
method="BFGS")
+ )
user system elapsed
4191.258 391.390 4597.724
> 4597.724/60
[1] 76.62873
taking just over 75 minutes to complete
> summary(reg.splm.random)
ML panel with , random effects, spatial error correlation
Call:
spreml(formula = formula, data = data, index = index, w =
listw2mat(listw),
w2 = listw2mat(listw2), lag = lag, errors = errors, cl = cl,
method = "BFGS")
Residuals:
Min. 1st Qu. Median Mean 3rd Qu. Max.
-5.75e-03 -1.08e-03 2.42e-05 -7.50e-06 1.07e-03 8.02e-03
Error variance parameters:
Estimate Std. Error t-value Pr(>|t|)
phi 0.045798 NaN NaN NaN
rho 0.725055 NaN NaN NaN
Coefficients:
Estimate Std. Error t-value Pr(>|t|)
(Intercept) 1.0284e-02 5.0441e-05 203.8892 < 2.2e-16 ***
I.score 5.2369e-03 1.0438e-03 5.0173 5.239e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
The code involves inversion of the nxn matrix I - \lambda W in each call
to the log likelihood function, hence the long run time. I've added the
splm maintainer to CC in case this thread didn't yet reach him. I think
that checking that lambda is finite and returning an infinite ll value if
not may work, but the documentation of maxLik() and nlminb would need
checking to see how to signal an invalid lambda.
Hope this clarifies,
Roger
PS. With traceback, it is as simple as setting debug(splm:::semREmod) and
then setting more debug()s - reading the code also helps; patience is
however essential.
> 6: invSigma(philambda, n, t., w2)
> 5: objective(.par, ...)
> 4: nlminb(start = myparms0, objective = ll.c, gradient = NULL, hessian = NULL,
> y = y, X = X, n = n, t. = t., w = w, w2 = w2, scale = parscale,
> control = list(x.tol = x.tol, rel.tol = rel.tol, trace = trace),
> lower = lower.bounds, upper = upper.bounds)
> 3: est.fun(X, y, ind, tind, n, k, t, nT, w = w, w2 = w2, coef0 = coef0,
> hess = hess, trace = trace, x.tol = x.tol, rel.tol = rel.tol,
> ...)
> 2: spreml(formula = formula, data = data, index = index, w = listw2mat(listw),
> w2 = listw2mat(listw2), lag = lag, errors = errors, cl = cl,
> ...)
> 1: spml(formula = mx.standard ~ I.score, data = analysis.subset,
> listw = listw.wgts, effect = "individual", model = "random",
> lag = FALSE, spatial.error = "b", index = c("Group", "Year"))
>
>
>
> My sessionInfo:
>
> R version 4.2.2 (2022-10-31 ucrt)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
> Running under: Windows 10 x64 (build 19044)
>
>
> Matrix products: default
>
>
> locale:
> [1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8 LC_MONETARY=English_United States.utf8
> [4] LC_NUMERIC=C LC_TIME=English_United States.utf8
>
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
>
> other attached packages:
> [1] splm_1.6-2 plm_2.6-2 spdep_1.2-7 spData_2.2.1 sp_1.6-0 forcats_1.0.0 stringr_1.5.0 dplyr_1.1.0 purrr_1.0.1
> [10] readr_2.1.4 tidyr_1.3.0 tibble_3.1.8 ggplot2_3.4.1 tidyverse_1.3.2 sf_1.0-9
>
>
> loaded via a namespace (and not attached):
> [1] nlme_3.1-160 fs_1.6.1 spatialreg_1.2-6 lubridate_1.9.2 httr_1.4.4 tools_4.2.2 backports_1.4.1
> [8] utf8_1.2.3 R6_2.5.1 KernSmooth_2.23-20 DBI_1.1.3 colorspace_2.1-0 withr_2.5.0 tidyselect_1.2.0
> [15] compiler_4.2.2 cli_3.6.0 rvest_1.0.3 expm_0.999-7 xml2_1.3.3 sandwich_3.0-2 scales_1.2.1
> [22] lmtest_0.9-40 classInt_0.4-8 proxy_0.4-27 digest_0.6.31 pkgconfig_2.0.3 dbplyr_2.3.0 collapse_1.9.2
> [29] ibdreg_0.3.8 rlang_1.0.6 readxl_1.4.2 rstudioapi_0.14 generics_0.1.3 zoo_1.8-11 jsonlite_1.8.4
> [36] googlesheets4_1.0.1 magrittr_2.0.3 Formula_1.2-4 s2_1.1.2 dotCall64_1.0-2 Matrix_1.5-3 Rcpp_1.0.10
> [43] munsell_0.5.0 fansi_1.0.4 lifecycle_1.0.3 stringi_1.7.8 MASS_7.3-58.1 grid_4.2.2 parallel_4.2.2
> [50] bdsmatrix_1.3-6 crayon_1.5.2 deldir_1.0-6 lattice_0.20-45 haven_2.5.1 splines_4.2.2 hms_1.1.2
> [57] pillar_1.8.1 boot_1.3-28 LearnBayes_2.15.1 wk_0.7.1 reprex_2.0.2 glue_1.6.2 modelr_0.1.10
> [64] vctrs_0.5.2 spam_2.9-1 tzdb_0.3.0 Rdpack_2.4 miscTools_0.6-26 cellranger_1.1.0 gtable_0.3.1
> [71] assertthat_0.2.1 rbibutils_2.2.13 broom_1.0.3 e1071_1.7-13 coda_0.19-4 class_7.3-20 googledrive_2.0.0
> [78] gargle_1.3.0 units_0.8-1 maxLik_1.5-2 timechange_0.2.0 ellipsis_0.3.2
>
>
>
> I tried running the same code on Linux x64 platform as well, with much the same end result.
> R version 4.2.2 Patched (2022-11-10 r83330)
> Platform: x86_64-pc-linux-gnu (64-bit)
> Running under: Ubuntu 18.04.6 LTS
>
>
> Here is the link to the minimally reproducible example (code and the actual data):
> https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.dropbox.com%2Fsh%2Fs680xpvfdxowuor%2FAAAH5yF4JtrzWUgdbvQIF6LBa%3Fdl%3D0&data=05%7C01%7Croger.bivand%40nhh.no%7C7b2114f83ed64bb06aad08db0f85b68f%7C33a15b2f849941998d56f20b5aa91af2%7C0%7C0%7C638120839199952772%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=QX%2BWBZkxcnNypTVT%2FmJTZJC1aUmDluawNH3LGOVosTE%3D&reserved=0
>
>
> Thank you for your help.
>
>
> Denys Dukhovnov
>
>
>
> On Wednesday, February 15, 2023 at 11:12:31 AM EST, Roger Bivand <roger.bivand using nhh.no> wrote:
>
>
>
>
>
> On Wed, 15 Feb 2023, Denys Dukhovnov via R-sig-Geo wrote:
>
>> Dear community,
>>
>> I am trying to run a spatial panel random effects SEM model using splm
>> package on a balanced spatial panel of N = 2472 and T = 4, and weights
>> are based on k = 6 nearest neighbors. I encounter this error, which I
>> can't find anything about in the documentation or online.
>>
>> spml(formula = mx.standard ~ I.score,
>> data = analysis.subset,
>> listw = listw.wgts,
>> effect = "individual",
>> model = "random",
>> lag = FALSE,
>> spatial.error = "b",
>> index = c("Group", "Year"))
>>
>> Error in .C64("aplsb1", SIGNATURE = c(SS$signature, SS$signature,
>> "double", : NAs in argument 7 and 'NAOK = FALSE' (dotCall64)
>
> Please at least provide the output of traceback() after the error (it does
> not crash, it error-exits correctly). Also provide the output of
> sessionInfo() - versions of underlying packages may matter (I'm thinking
> of dotCall64 and packages it uses). .C64() is not called by splm functions
> directly.
>
> Does the error persist on a fully updated system on the same OS?
>
> What happens on a different platform if available?
>
> Ideally, provide a fully reproducible minimal example using built-in data,
> or provide your data and the code used to create analysis.subset and
> listw.wgts, so that the running the code creating the error can be
> reproduced exactly. The error message reports NAs, are the data complete?
>
> Roger
>
>
>>
>> Unlike the same specification but with fixed effects (with model =
>> "within" argument), the one above takes a long while to run until it
>> crashes. As far as I can tell, there are no memory issues.
>>
>> An alternative spatial random effects using spgm() command runs OK, as
>> do non-spatial fixed and random effects models using plm(). For the one
>> above I could use spgm(), but I would prefer to keep all my models in
>> the maximum likelihood estimation for consistency.
>>
>> Any clarifications as to the nature of the error are welcome.
>>
>> Thank you.
>>
>>
>> Denys Dukhovnov
>>
>> _______________________________________________
>> R-sig-Geo mailing list
>> R-sig-Geo using r-project.org
>> https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-sig-geo&data=05%7C01%7Croger.bivand%40nhh.no%7C7b2114f83ed64bb06aad08db0f85b68f%7C33a15b2f849941998d56f20b5aa91af2%7C0%7C0%7C638120839199952772%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=XEUJSidD5%2FFjLSMxlLy%2BX%2FOijPwhkBOyY0C2KnKl3DI%3D&reserved=0
>>
>
>
--
Roger Bivand
Emeritus Professor
Department of Economics, Norwegian School of Economics,
Postboks 3490 Ytre Sandviken, 5045 Bergen, Norway.
e-mail: Roger.Bivand using nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
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