briencj / asremlplus Goto Github PK
View Code? Open in Web Editor NEWasremlPlus is an R package that augments the use of 'ASReml-R' and 'ASReml4-R' in fitting mixed models
License: Other
asremlPlus is an R package that augments the use of 'ASReml-R' and 'ASReml4-R' in fitting mixed models
License: Other
Hi, when trying to use the estimateV.asreml
function on a model object I get an error message that Z %*% G
are not comformable. Manual says estimate.V
can handle cor/corh variance functions - any idea about a workaround?
My model is a fairly simple one:
asreml(myformula, random = ~box+corh(HEXP):boxor, data = myset, maxiter = 200)
(I simplified it from a more complex one with corgh() and some correlations constrained using the vcc
option - thought it might be the fault of vcc
but the simpler one also does not seem to work).
Any feedback appreciated!
Szymek
It would be nice if this function would accept multiple objects, similar to the AIC function. For example:
R> AIC(mm1,mm2)
df AIC
mm1 3 46708.52
mm2 4 46654.05
Is this related to asremlPlus?
"
current.asr <- lm
current.asrt <- as.asrtests(current.asr,NULL,NULL)
Error: C stack usage 15922800 is too close to the limit
"
Appreciate feedback.
Thanky you.
jahn
Is this related to asremlPlus?
"
current.asr <- lm
current.asrt <- as.asrtests(current.asr,NULL,NULL)
Error: C stack usage 15922800 is too close to the limit
"
Appreciate feedback.
Thanky you.
jahn
I'm not sure if this is a bug or if I'm making some silly mistake, but seems the argument transform.function
in predictPlus
is not backtransforming the predictions.
Here is a quick example:
library(asreml)
library(asremlPlus)
# fit a model
mod <- asreml(Yield ~ Variety, data = Oats.dat)
pred <- predictPlus(mod, classify = 'Variety')$predictions
# fit a model but with a transformed target
mod_trans <- asreml(sqrt(Yield) ~ Variety, data = Oats.dat)
pred_trans <- predictPlus(mod, classify = 'Variety', transform.function = 'sqrt')$backtransforms
pred == pred_trans
Variety predicted.value standard.error upper.Confidence.limit lower.Confidence.limit est.status
1 TRUE TRUE NA TRUE TRUE TRUE
2 TRUE TRUE NA TRUE TRUE TRUE
3 TRUE TRUE NA TRUE TRUE TRUE
As you can see, the backtransforms
object is equal to the predictions
(except for the standard.error
column that was set to NA).
My session info:
sessionInfo()
R version 4.3.1 (2023-06-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.2 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8
[8] LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: America/Chicago
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] asremlPlus_4.3.55 asreml_4.1.0.176 Matrix_1.6-0
loaded via a namespace (and not attached):
[1] utf8_1.2.3 generics_0.1.3 qqconf_1.3.2 robustbase_0.99-0 bitops_1.0-7 stringi_1.7.12 lattice_0.21-8 pracma_2.4.2
[9] magrittr_2.0.3 caTools_1.18.2 grid_4.3.1 RColorBrewer_1.1-3 iterators_1.0.14 foreach_1.5.2 doParallel_1.0.17 plyr_1.8.8
[17] jsonlite_1.8.7 opdisDownsampling_0.8.2 httr_1.4.6 fansi_1.0.4 scales_1.2.1 codetools_0.2-19 cli_3.6.1 rlang_1.1.1
[25] munsell_0.5.0 tools_4.3.1 parallel_4.3.1 reshape2_1.4.4 memuse_4.2-3 dplyr_1.1.2 colorspace_2.1-0 ggplot2_3.4.2
[33] dae_3.2.15 benchmarkme_1.0.8 vctrs_0.6.3 R6_2.5.1 lifecycle_1.0.3 stringr_1.5.0 MASS_7.3-60 pkgconfig_2.0.3
[41] pillar_1.9.0 gtable_0.3.3 data.table_1.14.8 glue_1.6.2 sticky_0.5.6.1 Rcpp_1.0.11 benchmarkmeData_1.0.4 DEoptimR_1.1-0
[49] tibble_3.2.1 tidyselect_1.2.0 rstudioapi_0.15.0 qqplotr_0.0.6 compiler_4.3.1 twosamples_2.0.1
Hello,
it seems that the function infoCriteria from asremlPlus is not compatible with the new asreml package (4.2.0.257).
I get this error:
infoCriteria(mget(model_objects), IClikelihood = "full")
Error: 'vpc.char' is not an exported object from 'namespace:asreml'
Is it possible to solve this issue?
Regards,
Dianne
Hi Chris,
I'm having an issue with asremlPlus since I updated to the latest version of R and RStudio. When I run the following code: as.asrtests(m_resistance2015) I get the following warning:
Error in .make_numeric_version(x, strict, .standard_regexps()$valid_numeric_version) :
invalid non-character version specification 'x' (type: double)
I have version 4.4.32 of asremlPlus, and version 4.2.0.302 of asreml.
Thanks in advance for helping me out.
Best wishes,
Fleur
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.