fixed issue with global environments

NAMESPACE

 # Generated by roxygen2: do not edit by hand
 
 export("%>%")
+export(calc_vif)
+export(explore_na)
+export(impute)
+export(test_tac)
 export(trafficlight)
+import(graphics)
 importFrom(magrittr,"%>%")

R/calc_vif.R

@@ -26,8 +26,8 @@ calc_vif <- function(x) {
 	for (v in 1:ncol(x)) {
 		v.name <- colnames(x)[v]
 		other.v.names <- colnames(x)[-v]
-		mod.formula <- as.formula(paste(v.name, "~", paste(other.v.names, collapse = "+")))
-		mod <- lm(mod.formula, data = x)
+		mod.formula <- stats::as.formula(paste(v.name, "~", paste(other.v.names, collapse = "+")))
+		mod <- stats::lm(mod.formula, data = x)
 		R2 <- summary(mod)$r.squared
 		result[v, "Rsquared"] <- R2
 		result[v, "Tolerance"] <- 1 - R2

R/explore_na.R

@@ -18,6 +18,7 @@
 #' @param respect logical; this argument controls whether a unit column-width is the
 #'   same physical measurement on the device as a unit row-height (default is TRUE).
 #'
+#' @import graphics
 #' @export
 #' @author Saskia A. Otto
 #' @examples
@@ -26,10 +27,10 @@
 #' colnames(mat) <- paste0("variable", 1:10)
 #' explore_na(x = mat, time = 1981:2000)
 #' colnames(mat) <- LETTERS[1:10]
-#' explore_na(x = mat, time = 1981:2000, madj_y = -1.5, hadj_y = 2, respect = FALSE)
+#' explore_na(x = mat, time = 1981:2000, madj_y = -2.5, hadj_y = 2, respect = FALSE)
 
 explore_na <- function(x, time = NULL, cex_x = 1, cex_y = 1,
-  madj_y = 0, hadj_y = 1, respect = TRUE,...){
+  madj_y = 0, hadj_y = 1, respect = TRUE){
 
   if(!is.null(time)) {
     rownames(x) <- time
@@ -48,7 +49,7 @@ explore_na <- function(x, time = NULL, cex_x = 1, cex_y = 1,
   x <- x[reverse,]
 
   # Data Map
-  layout(matrix(c(1,1,2,1,1,2,3,3,4), ncol=3, byrow = TRUE), widths = c(2,2,1.5),
+  layout(matrix(c(1,1,2,1,1,2,3,3,4), ncol=3, byrow = TRUE), widths = c(2.5,2,1.5),
     heights = c(2,1,1.5), respect = respect)
   # graphics::layout(matrix(c(1,1,1,1), ncol = 2), widths = c(3.5,3.5), heights = c(2,2),
   #   respect = respect)
@@ -68,7 +69,7 @@ explore_na <- function(x, time = NULL, cex_x = 1, cex_y = 1,
   title(xlab="Number of years", line=2, cex.lab=1.2)
 
   #barplot stations
-  par(mar = c(4, 5+madj_y, 1.5, .5))
+  par(mar = c(4, 7+madj_y, 1.5, .5))
   barplot(apply(x>0, 2, sum), ylab = "",
     las = 2, cex.axis = cex_y, space = 0, col = "#db7170", xaxs = "i")
   title(ylab="Number of variables", line=2.5, cex.lab=1.2)

man/calc_vif.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/calc_vif.R
+\name{calc_vif}
+\alias{calc_vif}
+\title{Calculate the variance inflation factors}
+\usage{
+calc_vif(x)
+}
+\arguments{
+\item{x}{matrix or data frame containing only numerical variables.}
+}
+\value{
+The function returns a matrix with 3 columns:
+\describe{
+  \item{\code{Rsquared}}{}
+  \item{\code{Tolerance}}{}
+  \item{\code{VIF}}{}
+ }
+}
+\description{
+Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy
+eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam
+voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet
+clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.
+}
+\examples{
+x <- data.frame(a = 1:20, b = 1:20*2 + rnorm(20) )
+calc_vif(x)
+}

man/explore_na.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/explore_na.R
+\name{explore_na}
+\alias{explore_na}
+\title{Create multiple plots to explore gaps in the time series}
+\usage{
+explore_na(
+  x,
+  time = NULL,
+  cex_x = 1,
+  cex_y = 1,
+  madj_y = 0,
+  hadj_y = 1,
+  respect = TRUE
+)
+}
+\arguments{
+\item{x}{matrix or data frame containing time series of multiple variables.}
+
+\item{time}{vector of time units that will be used for the x ax}
+
+\item{cex_x}{double; the magnification to be used for the x labels relative to the
+current setting of cex.}
+
+\item{cex_y}{double; the magnification to be used for the y labels relative to the
+current setting of cex.}
+
+\item{madj_y}{double; adjustment of left margin relative to the
+current setting for longer or short variable names in the image plot and right barplot.}
+
+\item{hadj_y}{double; horizontal adjustment of the y labels in the image plot.}
+
+\item{respect}{logical; this argument controls whether a unit column-width is the
+same physical measurement on the device as a unit row-height (default is TRUE).}
+}
+\description{
+This function creates an image plot where available values for the different variables and years
+are indicated in gray and missing values in white. At the right side and bottom, two barplots
+are added showing the frequency of available variables per year and the available years per
+variable.
+}
+\examples{
+mat <- matrix(1:200, ncol = 10)
+mat[sample(1:200, sample(10:80, 1))] <- NA
+colnames(mat) <- paste0("variable", 1:10)
+explore_na(x = mat, time = 1981:2000)
+colnames(mat) <- LETTERS[1:10]
+explore_na(x = mat, time = 1981:2000, madj_y = -2.5, hadj_y = 2, respect = FALSE)
+}
+\author{
+Saskia A. Otto
+}

man/impute.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/impute.R
+\name{impute}
+\alias{impute}
+\title{Imputation of missing values by local mean substitution}
+\usage{
+impute(x, n = 2)
+}
+\arguments{
+\item{x}{numeric vector containing NAs.}
+
+\item{n}{integer; the number of previous and following values to be included in the mean.
+The default is 2 so the mean is based on a 5yr-period (including the year of the missing
+value).}
+}
+\value{
+The function returns the same numeric input vector, but with replaced missing values.
+}
+\description{
+The function substitutes missing values in time series with a mean of the \emph{n} previous and following years
+(or less depending on the position of NAs, whether it is at the beginning or end of the time series, and
+the presence of further NAs in the selected time period).
+}
+\examples{
+x <- c(NA, 1, 4, 2, 5, NA, 9, NA, 12, 11, NA)
+impute(x)
+}
+\author{
+Saskia A. Otto
+}

man/test_tac.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/test_tac.R
+\name{test_tac}
+\alias{test_tac}
+\title{Compute (partial) autocorrelation functions and test for significance}
+\usage{
+test_tac(x)
+}
+\arguments{
+\item{x}{numeric; an evenly spaced time vector which should be tested for temporal
+autocorrelation. Temporal gaps should be included as NAs.}
+}
+\value{
+The function returns a list with 2 components:
+\describe{
+  \item{\code{tac}}{TRUE if any lag in the (partial) autocorrelation functions
+    is significantly correlated (if correlation value > 0.4), else FALSE.}
+  \item{\code{max_lag}}{The maximal lag that is correlated.}
+ }
+}
+\description{
+Compute (partial) autocorrelation functions and test for significance
+}
+\examples{
+test_tac(x = 1:20)
+test_tac(x = rnorm(20))
+
+}

man/trafficlight.Rd

@@ -63,7 +63,7 @@ numeric vector of probabilities with values in [0,1]. (Values up to
 \item{quantile_type}{an integer between 1 and 9 selecting one of the nine quantile
 algorithms detailed below to be used. Default is 7 (see also \code{\link{quantile}}).}
 
-\item{intervals}{logical; number of evenly-spaced intervals. Default is 5.}
+\item{intervals}{logical; number of evenly spaced intervals. Default is 5.}
 
 \item{cols}{a character vector with colors for each quantile or interval.}