Add dataset of a group of experiments, Pimentel pg 147.

R/legTools.R

@@ -816,3 +816,52 @@ NULL
 #'        xlab="Nutrient level")
 #'
 NULL
+
+#' @name cottonFert
+#'
+#' @title A set of experiments in different locations studing NK on cotton
+#'
+#' @description These data is a set of experiments carried out in
+#'     different locations studing NK fertilization in cotton. All the 5
+#'     experiments are a complete randomized design with 4 replications
+#'     and 5 levels of fertilization based on N and K levels and a
+#'     control.
+#'
+#' \itemize{
+#'   \item \code{trt} unordered factor, treatment that consist of 4
+#'     cells from a 2^2 factorial design (\eqn{N\times K}) and a
+#'     control.
+#'   \item \code{rept} integer, indexes experimental units.
+#'   \item \code{loc} an unordered factor representing the locations
+#'     where the experiment was carried out.
+#'   \item \code{y} numeric, the response variable of the
+#'     experiment. The text book didn't give details.
+#' }
+#'
+#' @docType data
+#'
+#' @keywords datasets
+#'
+#' @usage data(cottonFert)
+#'
+#' @format a \code{data.frame} with 100 records and 4 variables.
+#'
+#' @source Pimentel Gomes, F. (2009). Curso de Estatística Experimental
+#'     (15th ed.). Piracicaba, São Paulo: FEALQ. (page 142)
+#'
+#' @examples
+#'
+#' library(lattice)
+#'
+#' data(cottonFert)
+#' str(cottonFert)
+#'
+#' xyplot(y~trt|loc,
+#'        data=cottonFert, type=c("p", "a"),
+#'        ylab="y", xlab="Treatment")
+#'
+#' xyplot(log(y)~trt|loc,
+#'        data=cottonFert, type=c("p", "a"),
+#'        ylab="y", xlab="Treatment")
+#'
+NULL

data-raw/cottonFert.R

+##----------------------------------------------------------------------
+## Data generation.
+
+cottonFert <- expand.grid(
+    ## K=c(-1, 1),
+    ## N=c(-1, 1),
+    trt=c("N1K1", "N1K2", "N2K1", "N2K2", "CTRL"),
+    rept=1:4,
+    loc=gl(5, 1),
+    KEEP.OUT.ATTRS=FALSE)
+
+## x <- scan()
+## dput(x/10)
+
+cottonFert$y <- c(4.2, 3.6, 3.2, 3.6, 2.4, 2.4, 2.2, 2.6, 2.8, 1.2, 2.8,
+                  1.8, 3, 3, 3, 3.2, 3.2, 2, 2.4, 2.8, 11, 10, 12, 10.5,
+                  8.5, 10.5, 9.5, 9, 11.5, 8, 9, 9, 9.5, 10.5, 10, 9, 8,
+                  9.5, 10, 7, 7, 8.5, 9, 9, 7, 7.5, 7, 6, 9.5, 7, 6.5,
+                  8, 6, 8, 4.5, 5.5, 5.5, 5.5, 7, 6, 8, 8, 7, 9, 3.5,
+                  6.9, 5.5, 4.7, 6.5, 3, 6, 7.5, 5.5, 5.5, 3.9, 6.5, 8,
+                  9, 7, 7, 1.72, 2.38, 2.52, 2.78, 1.48, 1.81, 2.56,
+                  2.88, 3.01, 1.62, 1.73, 2.48, 2.76, 2.83, 1.58, 1.62,
+                  2.43, 2.54, 2.79, 1.56)
+
+## Check using the totals.
+aggregate(y~loc, data=cottonFert, FUN=sum)
+
+str(cottonFert)
+
+save(cottonFert, file="../data/cottonFert.RData")
+
+##----------------------------------------------------------------------
+## Examples.
+
+library(lattice)
+
+data(cottonFert)
+str(cottonFert)
+
+xyplot(y~trt|loc,
+       data=cottonFert, type=c("p", "a"),
+       ylab="y", xlab="Treatment")
+
+xyplot(log(y)~trt|loc,
+       data=cottonFert, type=c("p", "a"),
+       ylab="y", xlab="Treatment")
+
+m0 <- by(data=cottonFert, INDICES=cottonFert$loc,
+         FUN=lm, formula=y~trt)
+lapply(m0, anova)
+
+m1 <- lm(y~loc*trt, data=cottonFert)
+
+par(mfrow=c(2,2)); plot(m1); layout(1)
+MASS::boxcox(m1)
+
+m2 <- lm(log(y)~loc*trt, data=cottonFert)
+par(mfrow=c(2,2)); plot(m2); layout(1)
+anova(m2)

man/cottonFert.Rd

+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/legTools.R
+\docType{data}
+\name{cottonFert}
+\alias{cottonFert}
+\title{A set of experiments in different locations studing NK on cotton}
+\format{a \code{data.frame} with 100 records and 4 variables.}
+\source{
+Pimentel Gomes, F. (2009). Curso de Estatística Experimental
+    (15th ed.). Piracicaba, São Paulo: FEALQ. (page 142)
+}
+\usage{
+data(cottonFert)
+}
+\description{
+These data is a set of experiments carried out in
+    different locations studing NK fertilization in cotton. All the 5
+    experiments are a complete randomized design with 4 replications
+    and 5 levels of fertilization based on N and K levels and a
+    control.
+
+\itemize{
+  \item \code{trt} unordered factor, treatment that consist of 4
+    cells from a 2^2 factorial design (\eqn{N\times K}) and a
+    control.
+  \item \code{rept} integer, indexes experimental units.
+  \item \code{loc} an unordered factor representing the locations
+    where the experiment was carried out.
+  \item \code{y} numeric, the response variable of the
+    experiment. The text book didn't give details.
+}
+}
+\examples{
+library(lattice)
+
+data(cottonFert)
+str(cottonFert)
+
+xyplot(y~trt|loc,
+       data=cottonFert, type=c("p", "a"),
+       ylab="y", xlab="Treatment")
+
+xyplot(log(y)~trt|loc,
+       data=cottonFert, type=c("p", "a"),
+       ylab="y", xlab="Treatment")
+}
+\keyword{datasets}
+