Description Usage Arguments Value Author(s) Examples
Cross validation results for a model
1 2 3 |
clinical_x |
clinical variables that will always be included in the model |
genomic_x |
genomic variables that will be penalized if a penalized model is used |
y |
response variables |
data |
dataframe if clinical formula is used |
clinical_formula |
formula for clinical variables |
family |
gaussian, binomial or poisson |
folds |
predefined partions for cross validation |
k |
number of cross validation folds. A value of k=n is leave one out cross validation. |
fit_method |
glm or glmnet used to fit the model |
method_name |
tracking variable to include in return dataframe |
n.cores |
Number of cores to be used |
... |
additional commmands to glm or cv.glmnet |
returns a dataframe of predicted values and observed values. In addition, method_name is recorded if that variable is defined.
Ben Sherwood <ben.sherwood@ku.edu>
1 2 3 4 5 6 | x <- matrix(rnorm(800),ncol=8)
y <- runif(100) < exp(1 + x[,1] + x[,5])/(1+exp(1 + x[,1] + x[,5]))
cv_results <- cv(x,y=y,method_name="without_formula")
combined_data <- data.frame(y=y,x1=x[,1],x5=x[,5])
gx <- x[,c(2,3,4,6,7,8)]
cvf <- cv(genomic_x=gx,clinical_formula=y~x1+x5,data=combined_data,method_name="with_form")
|
Loading required package: glmnet
Loading required package: Matrix
Loading required package: foreach
Loaded glmnet 2.0-12
Loading required package: parallel
Loading required package: pROC
Type 'citation("pROC")' for a citation.
Attaching package: 'pROC'
The following object is masked from 'package:glmnet':
auc
The following objects are masked from 'package:stats':
cov, smooth, var
Warning message:
In data.row.names(row.names, rowsi, i) :
some row.names duplicated: 11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100 --> row.names NOT used
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