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The new home of RCov on GitHub
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- This method is called when there is a non - line .
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Trending Discussions on rcov
QUESTION
I have a multivariate model with this (approximate) form:
...ANSWER
Answered 2021-May-21 at 01:08The gelman.diag
requires a mcmc.list
. If we are running models with different set of parameters, extract the 'Sol' and place it in a list
(Below, it is the same model)
QUESTION
I am trying to get the r2 values for each marker in a GWAS using the GWAS function in the r package "sommer". From the documentation I see they should be in the object mix1$scores: scores A dataframe with as many columns as markers analyzed and 5 rows containingthe following:beta: marker effects.score: marker scores (-log_10p) for the traits.Fstat: F-statistic associated to the test.R2: R2 value for each marker.R2s: R2 value for each marker scaled
However, in my model, only marker scores are listed.
Example:
...ANSWER
Answered 2021-Mar-23 at 13:59the GWAS function was refactored to use C++ code starting from 4.1.2 and some additional metrics like r2 were removed from the output. Those additional metrics will be brought back for 4.1.3. On the meantime, you can always go back to versions 4.1.1 or older to get that metric.
Cheers, Eduardo
QUESTION
In the newest version of the sommer package, some adaptations to the predict function have been made, unfortunately, I am having issues with it in the newest version.
if I do not specify any classify variable:
predict.mmer(modelh) Error in strsplit(classify, ":") : non-character argument
predict.mmer(modelh, classify = "GEN")
Error in [.data.frame
(object$dataOriginal, , c(colnames(DTX), ignored, :
undefined columns selected
my model looks like this:
mmer(data = data, fixed = value ~ 1 , random = ~ GEN + ROWf + COLf + spl2D(ROW,COL), rcov = ~vs(units))
further question: in the model above, I am getting all the same values in the model$fitted vector, which is equal to the intercept. As I understand, the fitted value should also include random effects like GEN, ROWf, ... . Am I misunderstanding something here?
Appreciate any advice, Best Regards, Hermann
...ANSWER
Answered 2020-Nov-11 at 04:29since the 4.1.1 version the predict function is not used anymore to get fitted values, but to obtain adjusted means for an specific classify argument. Therefore, the classify argument cannot be skipped.
If you need fitted values now the fitted() function should return what you're looking for.
Now, the issue with using the classify must come from the use of the spl2D() function outside of the vs() function. You may want to download the newest version from GitHub (version 4.1.2) and try with:
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