updated the time_pls function

NAMESPACE

@@ -3,6 +3,7 @@
 export(combine_sites)
 export(daily_pls)
 export(is_valid_pH)
+export(time_pls)
 import(assertive)
 import(dplyr)
 import(ggplot2)

R/time_pls.R

@@ -1,10 +1,23 @@
 
-# data <- data
-# dates <- data$date
-# y <- data$cfs
-# X <- cbind(data$p,data$tmin,data$tmax)
-
-time_pls <- function(y,X,dates,lag=365,ncomps=3) {
+#' @title time_pls
+#' @description Performs pls regression on time series data for a given number of lags.
+#' @param y Vector of variable to predict using pls
+#' @param X Matrix of covariates for pls
+#' @param lag Number of lags to be used for creating pls components
+#' @param ncomps Number of components for pls regression
+#' @import plsdepot
+#' @import assertive
+#' @examples
+#' \dontrun{
+#' data <- data
+#' dates <- data$date
+#' y <- data$cfs
+#' X <- cbind(data$p,data$tmin,data$tmax)
+#' plsm1 <- time_pls(y,X,dates,lag=30,ncomps=3)
+#' }
+#' @export
+
+time_pls <- function(y,X,dates,lag=30,ncomps=3) {
 
   mutate <- dplyr::mutate
 
@@ -25,6 +38,7 @@ time_pls <- function(y,X,dates,lag=365,ncomps=3) {
 
   # run partial least squares regression
   pls_model <- plsreg1(X, y, comps = ncomps)
+  pls_model$dates <- dates
   return(pls_model)
 
   # month <- data$month[(lag+1):nrow(data)]

tests/testthat/test-time_pls.R

@@ -0,0 +1,5 @@
+context("time series pls")
+
+test_that("time_pls function exists", {
+  expect_true(is.function(time_pls))
+})