viraltab {viralmodels} | R Documentation |
Competing models table
Description
Trains and optimizes a series of regression models for viral load or CD4 counts
Usage
viraltab(
traindata,
semilla,
target,
viralvars,
logbase,
pliegues,
repeticiones,
rejilla
)
Arguments
traindata |
A data frame |
semilla |
A numeric value |
target |
A character value |
viralvars |
Vector of variable names related to viral data. |
logbase |
The base for logarithmic transformations. |
pliegues |
A numeric value |
repeticiones |
A numeric value |
rejilla |
A numeric value |
Value
A table of competing models
Examples
library(dplyr)
library(baguette)
library(kernlab)
library(kknn)
library(ranger)
library(rules)
library(glmnet)
# Define the function to impute values in the undetectable range
impute_undetectable <- function(column) {
set.seed(123)
ifelse(column <= 40,
rexp(sum(column <= 40), rate = 1/13) + 1,
column)
}
library(viraldomain)
data("viral", package = "viraldomain")
viral_imputed <- viral |>
mutate(across(starts_with("vl"), ~impute_undetectable(.x)))
traindata <- viral_imputed
semilla <- 1501
target <- "cd_2022"
viralvars <- c("vl_2019", "vl_2021", "vl_2022")
logbase <- 10
pliegues <- 2
repeticiones <- 1
rejilla <- 1
set.seed(123)
viraltab(traindata, semilla, target, viralvars, logbase, pliegues, repeticiones, rejilla)
[Package viralmodels version 1.3.1 Index]