Extract predictions vectors of an object returned by clmm using multpile phenotypes

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Description

Takes an object returned by clmm using multpile phenotypes and returns a matrix of predicted values from every model. Every column represents the prediction vector of one model

Usage

1
get_pred(mod)

Arguments

mod

List returned by clmm using multpile phenotypes

Value

Matrix of prediction vectors in columns

See Also

clmm, get_cor, cCV

Examples

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### Running a 4-fold cross-validation with one repetition:
## Not run: 

# generate random data
rand_data(500,5000)

### compute the list of masked phenotype-vectors for CV
y_CV <- cCV(y,fold=4,reps=1)


### Cross Validation using GBLUP
G.A <- cgrm.A(M,lambda=0.01)


### generate the list of design matrices for clmm
Z_list = list(t(chol(G.A)))

### specify options
h2 = 0.3
scale = unlist(lapply(y_CV,function(x)var(x,na.rm=T))) * h2
df = rep(5,length(y_CV))
par_random = list(list(method="ridge",scale=scale,df=df))

### run 
fit <- clmm(y_CV, Z=Z_list, par_random=par_random, niter=5000, burnin=2500)

### inspect results
str(fit)

### obtain predictions
pred <- get_pred(fit)

### prediction accuracy
get_cor(pred,y_CV,y)

## End(Not run)