Merge branch 'feature/4' into 'devel'

Feature/4

Adds functions used by @wbonat in a recent paper.

See merge request !8

DESCRIPTION

 Package: legTools
 Title: Convenience Functions, Small GUI to Teach Statistics and Some Datasets
-Version: 0.1.1
+Version: 0.1.2
 Authors@R: person("LEG", "Core Team", email = "leg@ufpr.br", role =
     c("aut", "cre"))
 Description: legTools is a collection of R functions and datasets used for
@@ -11,11 +11,14 @@ Description: legTools is a collection of R functions and datasets used for
 Depends:
     R (>= 3.2.1)
 Imports:
-    lattice
+    lattice,
+    latticeExtra
 Depends:
     gWidgets,
     gWidgetstcltk,
-    knitr
+    knitr,
+    markdown,
+    RWordPress
 License: GPL-3 | file LICENSE
 URL: http://git.leg.ufpr.br/leg/legTools
 BugReports: http://git.leg.ufpr.br/leg/legTools/issues

NAMESPACE

 # Generated by roxygen2 (4.1.1): do not edit by hand
 
 export(biasBox)
+export(knit2wpCrayon)
 export(loessGui)
+export(panel.segplot.by)
 export(polyGui)
 export(runAllChunks)
 export(subsetDropAll)
 export(twoStripCombined)
+export(yscale.component.right)
+import(RWordPress)
 import(gWidgets)
 import(gWidgetstcltk)
 import(knitr)
 import(lattice)
+import(latticeExtra)
+import(markdown)

R/knit2wpCrayon.R

@@ -2,8 +2,9 @@
 #'
 #' @name knit2wpCrayon
 #'
-#' @description This function improves the \code{RWordPress::knit2wp} to
-#'     allow properly render code when using Crayon Sintax Highlighter.
+#' @description This function improves \code{RWordPress::knit2wp} to
+#'     allow properly render code when using Crayon Sintax Highlighter
+#'     in Wordpress.
 #'
 #' @param input a markdown or Rmarkdown file.
 #' @param title title for the post.
@@ -16,15 +17,15 @@
 #' @param upload logical, if the file is to be updated to the blog.
 #' @param publish logical, if the post is to be published or stay in
 #'     draft mode.
-#' @param write logical, is the result of knit be written to a html
-#'     file. This is useful to copy from this file and paste inside the
-#'     wordpress post editor (on text mode, not visual mode).
+#' @param write logical, if the result of knit should be written to a
+#'     html file. This is useful to copy from this file and paste inside
+#'     the Wordpress editor (on text mode, not visual mode).
 #'
-#' @return None is returned by the function.
+#' @return Nothing is returned by the function.
 #'
 #' @author Walmes Zeviani, \email{walmes@@ufpr.br}
 #'
-#' @import knitr RWordPress
+#' @import knitr markdown RWordPress
 #' @export
 #' @examples
 #' \donttest{
@@ -53,19 +54,35 @@ knit2wpCrayon <- function(input, title="A post from knitr", ...,
                           action=c("newPost", "editPost", "newPage"),
                           postid, encoding=getOption("encoding"),
                           upload=FALSE, publish=FALSE, write=TRUE){
+    ##
+    ##-------------------------------------------
+    ## Loading required packages.
+    ##
+    if (!requireNamespace("knitr", quietly=TRUE)){
+        stop("`knitr` needed for this function to work. Please install it.",
+             call.=FALSE)
+    }
+    if (!requireNamespace("markdown", quietly=TRUE)){
+        stop("`markdown` needed for this function to work. Please install it.",
+             call.=FALSE)
+    }
+        if (!requireNamespace("RWordPress", quietly=TRUE)){
+        stop("`RWordPress` needed for this function to work. Please install it.",
+             call.=FALSE)
+    }
     out <- knit(input, encoding=encoding)
     on.exit(unlink(out))
     con <- file(out, encoding=encoding)
     on.exit(close(con), add=TRUE)
-    content <- knitr:::native_encode(readLines(con, warn=FALSE))
+    content <- native_encode(readLines(con, warn=FALSE))
     content <- paste(content, collapse="\n")
-    content <- markdown::markdownToHTML(text=content, fragment.only=TRUE)
+    content <- markdownToHTML(text=content, fragment.only=TRUE)
     content <- gsub(
         pattern="<pre><code class=\"([[:alpha:]]+)\">(.+?)</code></pre>",
         replacement="<pre class=\"lang:\\1 decode:true\">\\2</pre>",
         x=content)
-    content=knitr:::native_encode(content, "UTF-8")
-    title=knitr:::native_encode(title, "UTF-8")
+    content=native_encode(content, "UTF-8")
+    title=native_encode(title, "UTF-8")
     if (write){
         writeLines(text=content,
                    con=gsub(x=out, pattern="\\.md$", replacement=".html"))

R/legTools.R

@@ -13,10 +13,11 @@ NULL
 #'
 #' @description This is an artifial dataset corresponding a experiment
 #'     to study the effect of feeding type (factor with 4 categorical
-#' nominal levels) in pig weight gain. The experiment was a randomized
-#' complete design with five experimental units per treatment level. The
-#' experimental unit was a pig. The response measured was weight gain
-#' from the beggining to the end of the experiment.
+#'     nominal levels) in pig weight gain. The experiment was a
+#'     randomized complete design with five experimental units per
+#'     treatment level. The experimental unit was a pig. The response
+#'     measured was weight gain from the beggining to the end of the
+#'     experiment.
 #'
 #' \itemize{
 #'     \item \code{ft} feeding type, a categorical factor with 4
@@ -32,8 +33,8 @@ NULL
 #'
 #' @format a \code{data.frame} with 20 records and 2 variables.
 #'
-#' @source Frederico, P. (2009). Curso de Estatística Experimental
-#' (15th ed.). Piracicaba, São Paulo: FEALQ. (page 62)
+#' @source Frederico, P. (2009). Curso de Estatística Experimental (15th
+#'     ed.). Piracicaba, São Paulo: FEALQ. (page 62)
 #'
 #' @examples
 #'
@@ -51,9 +52,9 @@ NULL
 #' @title Potato variety competition experiment
 #'
 #' @description These data are from an experiment done by the engineer
-#' Oscar A. Garay at Balcare, Argentina. The experiment was done in a
-#' randomized complete block design with 4 blocks. Potato yield (t/ha)
-#' was recorded in each experimental unit.
+#'     Oscar A. Garay at Balcare, Argentina. The experiment was done in
+#'     a randomized complete block design with 4 blocks. Potato yield
+#'     (t/ha) was recorded in each experimental unit.
 #'
 #' \itemize{
 #'     \item \code{block} a categorical unordered factor with 4 levels.
@@ -70,8 +71,8 @@ NULL
 #'
 #' @format a \code{data.frame} with 32 records and 3 variables.
 #'
-#' @source Frederico, P. (2009). Curso de Estatística Experimental
-#' (15th ed.). Piracicaba, São Paulo: FEALQ. (page 76)
+#' @source Frederico, P. (2009). Curso de Estatística Experimental (15th
+#'     ed.). Piracicaba, São Paulo: FEALQ. (page 76)
 #'
 #' @examples
 #' require(lattice)
@@ -89,12 +90,12 @@ NULL
 #' @title Plowing level on corn yield
 #'
 #' @description These data are from an experiment done by the engineer
-#' Duvilio Ometto to study the effect of plowing level on corn yield. It
-#' was used 2 levels of plowing: normal (or superficial) and deep. The
-#' experiment was done in a randomized complete block design with 6
-#' blocks. Corn yield (t/ha) was recorded in each experimental unit
-#' but in this experiment there was 2 experimental units for each factor
-#' level in each block.
+#'     Duvilio Ometto to study the effect of plowing level on corn
+#'     yield. It was used 2 levels of plowing: normal (or superficial)
+#'     and deep. The experiment was done in a randomized complete block
+#'     design with 6 blocks. Corn yield (t/ha) was recorded in each
+#'     experimental unit but in this experiment there was 2 experimental
+#'     units for each factor level in each block.
 #'
 #' \itemize{
 #'     \item \code{block} a categorical unordered factor with 6 levels.
@@ -110,8 +111,8 @@ NULL
 #'
 #' @format a \code{data.frame} with 24 records and 3 variables.
 #'
-#' @source Frederico, P. (2009). Curso de Estatística Experimental
-#' (15th ed.). Piracicaba, São Paulo: FEALQ. (page 91)
+#' @source Frederico, P. (2009). Curso de Estatística Experimental (15th
+#'     ed.). Piracicaba, São Paulo: FEALQ. (page 91)
 #'
 #' @examples
 #' require(lattice)
@@ -122,3 +123,86 @@ NULL
 #'        xlab="Plowing level")
 #'
 NULL
+
+#' @name defoliation
+#'
+#' @title Bolls in cotton as function of artifitial defoliation
+#'
+#' @description This dataset contais the result of a real experiment to
+#'     evaluate the effect of artifitial defoliation in combination with
+#'     phenological stage of occurence on the production of cotton
+#'     represented by the number of bolls produced at the end of the
+#'     crop cycle. The experiment is a \eqn{5\times 5} factorial with 5
+#'     replications casualized at random to the experimental units (a
+#'     randomized complete design). The experimental unit was a pot with
+#'     2 plants. An interesting fact about this data is that the
+#'     response is a count variable that shows underdispersion (sample
+#'     variance less than the sample mean).
+#'
+#' \itemize{
+#' \item \code{phenol} a categorical ordered factor with 5 levels
+#'     that represent the phenological stages of the cotton plant in
+#'     which defoliation was applied.
+#' \item \code{defol} a numeric factor with 5 levels that represents the
+#'     artifical level of defoliation (percent in leaf area removed with
+#'     scissors) applied for all leaves in the plant.
+#' \item \code{rept} index for each experimenal unit in each treatment cell.
+#' \item \code{bolls} the number of bolls produced (count variable)
+#'     evaluated at harvest.
+#' }
+#'
+#' @details The experiment was done in a greenhouse at Universidade
+#'     Federal da Grande Dourados. Visit
+#' \itemize{
+#' \item 1) \code{http://www.cabdirect.org/abstracts/20123299470.html}
+#' \item 2) \code{http://leg.ufpr.br/doku.php/publications:papercompanions:zeviani-jas2014}
+#' }
+#' 1 for an article discussing the effect of defoliation on cotton yield and
+#'     visit 2 for an article that evaluate a count regression model able to
+#'     deal with the underdispersion. See the references section also.
+#'
+#' @docType data
+#'
+#' @keywords datasets
+#'
+#' @usage data(defoliation)
+#'
+#' @format a \code{data.frame} with 125 records and 4 variables.
+#'
+#' @references Silva, A. M., Degrande, P. E., Suekane, R., Fernandes,
+#'     M. G., & Zeviani, W. M. (2012). Impacto de diferentes níveis de
+#'     desfolha artificial nos estádios fenológicos do
+#'     algodoeiro. Revista de Ciências Agrárias, 35(1), 163–172.
+#'
+#' Zeviani, W. M., Ribeiro, P. J., Bonat, W. H., Shimakura, S. E., &
+#'     Muniz, J. A. (2014). The Gamma-count distribution in the analysis
+#'     of experimental underdispersed data. Journal of Applied
+#'     Statistics, 41(12),
+#'     1–11. http://doi.org/10.1080/02664763.2014.922168
+#'
+#' @examples
+#'
+#' library(lattice)
+#' library(latticeExtra)
+#'
+#' ## x11(width=7, height=2.8)
+#' xyplot(bolls~defol|phenol, data=defoliation,
+#'        layout=c(NA, 1), type=c("p", "smooth"),
+#'        xlab="Artificial defoliation level",
+#'        ylab="Number of bolls produced",
+#'        xlim=extendrange(c(0:1), f=0.15), jitter.x=TRUE)
+#'
+#' ## Sample mean and variance in each treatment cell.
+#' mv <- aggregate(bolls~phenol+defol, data=defoliation,
+#'                 FUN=function(x) c(mean=mean(x), var=var(x)))
+#' str(mv)
+#'
+#' xlim <- ylim <- extendrange(c(mv$bolls), f=0.05)
+#'
+#' ## Evidence in favor of the underdispersion.
+#' xyplot(bolls[,"var"]~bolls[,"mean"], data=mv,
+#'        aspect="iso", xlim=xlim, ylim=ylim,
+#'        ylab="Sample variance", xlab="Sample mean")+
+#'     layer(panel.abline(a=0, b=1, lty=2))
+#'
+NULL

R/panel.segplot.by.R

+#' @title Lattice panel to non overlapping segments in \code{segplot()}
+#'
+#' @name panel.segplot.by
+#'
+#' @description This panel allows no overlapping of segments in
+#'     \code{latticeExtra::segplot()} when using the argument groups.
+#'
+#' @param x,y,z,data,centers,subscripts,... see
+#'     \code{\link[latticeExtra]{segplot}}.
+#' @param groups the grouping variable. Must be a factor.
+#' @param f numeric, factor that is the vertical distance among
+#'     arrows. In general a value less than 1. Default is 0.05.
+#' @param rev logical, use the reverse order of the factor levels to
+#'     place the segments. Default is \code{FALSE}.
+#'
+#' @return None is returned.
+#'
+#' @seealso \code{\link[latticeExtra]{segplot}}
+#'
+#' @author Walmes Zeviani, \email{walmes@@ufpr.br}
+#'
+#' @export
+#'
+#' @examples
+#'
+#' library(latticeExtra)
+#'
+#' m0 <- lm(log(breaks)~wool*tension, data=warpbreaks)
+#' anova(m0)
+#' par(mfrow=c(2,2)); plot(m0); layout(1)
+#'
+#' pred <- data.frame(wool=c("A", "B", "A", "B", "A", "B"),
+#'                    tension=c("L", "L", "M", "M", "H", "H"))
+#'
+#' X <- matrix(c(1, 1, 1, 1, 1, 1,
+#'               0, 1, 0, 1, 0, 1,
+#'               0, 0, 1, 1, 0, 0,
+#'               0, 0, 0, 0, 1, 1,
+#'               0, 0, 0, 1, 0, 0,
+#'               0, 0, 0, 0, 0, 1), nrow=6, ncol=6)
+#'
+#' ## Estimate and standart error.
+#' ## X%*%coef(m0)
+#' ## sqrt(diag(X%*%vcov(m0)%*%t(X)))
+#'
+#' U <- chol(vcov(m0))
+#' pred$est <- X%*%coef(m0)
+#' pred$se <- sqrt(apply(X%*%t(U), MARGIN=1, FUN=function(x) sum(x^2)))
+#'
+#' tval <- qt(p=c(lwr=0.025, upr=0.975), df=df.residual(m0))
+#' pred <- cbind(pred, sweep(x=outer(pred$se, tval, "*"),
+#'                           MARGIN=1, STATS=pred$est, FUN="+"))
+#'
+#' ## Overlapping segments.
+#' segplot(wool~lwr+upr, centers=est, data=pred, draw=FALSE)
+#'
+#' ## Prefer ordering always before using "pch=".
+#' pred <- pred[with(pred, order(tension, wool)), ]
+#'
+#' segplot(tension~lwr+upr, data=pred,
+#'         centers=est, draw=FALSE,
+#'         ylab="Tension level",
+#'         xlab=expression("Estimate"%+-%"error margin for a 0.95 CI"),
+#'         groups=wool, f=0.05, rev=TRUE,
+#'         pch=as.integer(pred$wool),
+#'         panel=panel.segplot.by,
+#'         key=list(title="Type of wool", cex.title=1.1,
+#'                  text=list(levels(pred$wool)),
+#'                  lines=list(pch=1:2, lty=1),
+#'                  divide=1, type="o"))
+#'
+panel.segplot.by <- function(x, y, z, data, centers, subscripts,
+                             groups, f=0.05, rev=FALSE, ...){
+    if(!missing(data)){
+        da <- eval(data, envir=parent.frame())
+        groups <- da[, deparse(substitute(groups))]
+    }
+    d <- 2*((as.numeric(groups)-1)/(nlevels(groups)-1))-1
+    if (rev){
+        d <- rev(d)
+    }
+    z <- as.numeric(z)+f*d
+    panel.segplot(x, y, z, centers=centers,
+                  subscripts=subscripts, ...)
+}

R/yscale.components.right.R

+#' @title y-axis annotations on the right side
+#'
+#' @name yscale.components.right
+#'
+#' @description This function if for place y axis annotation on the
+#'     right side of the plot.
+#'
+#' @param ... arguments passed by the lattice function called. See
+#'     \link[lattice]{yscale.components.default}.
+#'
+#' @import lattice latticeExtra
+#'
+#' @source When such feature was necessary, a search in the web was done
+#'     and a post in the r-help mailing list inspired us
+#'     \code{http://r.789695.n4.nabble.com/Spacing-between-lattice-panels-td855613.html}.
+#'
+#' @author Walmes Zeviani, \email{walmes@@ufpr.br}
+#' 
+#' @export
+#'
+#' @examples
+#'
+#' library(lattice)
+#' library(latticeExtra)
+#' 
+#' ## alternating=2 works when relation="same".
+#' p1 <- xyplot(yield~K|N+P, data=npk,
+#'              scales=list(y=list(alternating=2)))
+#' useOuterStrips(p1)
+#' 
+#' ## y annotation don't is written on the right side.
+#' p2 <- xyplot(yield~K|N+P, data=npk,
+#'              scales=list(y=list(relation="free", alternating=2)))
+#' useOuterStrips(p2)
+#' 
+#' ## The desired result.
+#' p3 <- xyplot(yield~K|N+P, data=npk,
+#'              scales=list(y=list(relation="free", alternating=2)),
+#'              ylab=NULL, ylab.right="Yield",
+#'              yscale.component=yscale.component.right,
+#'              between=list(x=0.5, y=0.2),
+#'              par.settings=list(
+#'                  layout.widths=list(
+#'                      right.padding=-2,
+#'                      left.padding=-2,
+#'                      ylab.right=5),
+#'                  strip.background=list(col=c("gray50", "gray90"))),
+#'              )
+#' useOuterStrips(p3)
+#'
+yscale.component.right <- function(...){
+    ans <- yscale.components.default(...)
+    ans$right <- ans$left
+    ans$left <- NULL
+    ans
+}

buildPkg.R

@@ -30,7 +30,7 @@ check(cleanup = FALSE, manual = TRUE, vignettes = FALSE,
 # Run examples from all functions of the package
 # run_examples()
 # Run examples from a specific function
-# dev_example("loessGui")
+# dev_example("yscale.components.right")
 
 ## Show all exported objects.
 ls("package:legTools")

data-raw/defoliation.R

+##----------------------------------------------------------------------
+## Data generation.
+
+phenol <- c("vegetative", "flower bud", "blossom", "boll", "boll open")
+defoliation <- expand.grid(rept=1:5,
+                           defol=seq(0, 1, length.out=5),
+                           phenol=factor(phenol, levels=phenol),
+                           KEEP.OUT.ATTRS=FALSE)
+
+defoliation$bolls <- c(10, 9, 8, 8, 10, 11, 9, 10, 10, 10, 8, 8, 10, 8,
+                       9, 9, 7, 7, 8, 9, 8, 6, 6, 5, 6, 7, 8, 8, 9, 10,
+                       9, 12, 7, 10, 9, 8, 9, 9, 10, 8, 11, 10, 7, 8, 8,
+                       7, 7, 7, 7, 8, 10, 9, 8, 12, 8, 7, 5, 5, 7, 5, 6,
+                       5, 7, 4, 7, 8, 5, 7, 6, 4, 5, 5, 4, 4, 5, 8, 10,
+                       7, 8, 10, 9, 6, 6, 8, 6, 9, 7, 11, 8, 9,6, 6, 6,
+                       6, 7, 3, 3, 2, 4, 3, 11, 7, 9, 12 , 11, 9, 13, 8,
+                       10, 10, 9, 7, 7, 9, 9, 8, 8, 10, 8, 10, 9, 8, 10,
+                       8, 10)
+
+defoliation <- defoliation[,c(3,2,1,4)]
+str(defoliation)
+save(defoliation, file="../data/defoliation.RData")
+rm(list=ls())
+load(file="../data/defoliation.RData")
+ls()
+
+##----------------------------------------------------------------------
+## Examples.
+
+library(lattice)
+library(latticeExtra)
+
+x11(width=7, height=2.8)
+xyplot(bolls~defol|phenol, data=defoliation,
+       layout=c(NA, 1), type=c("p", "smooth"),
+       xlab="Artificial defoliation level",
+       ylab="Number of bolls produced",
+       xlim=extendrange(c(0:1), f=0.15), jitter.x=TRUE)
+
+## Sample mean and variance in each treatment cell.
+mv <- aggregate(bolls~phenol+defol, data=defoliation,
+                FUN=function(x) c(mean=mean(x), var=var(x)))
+str(mv)
+
+xlim <- ylim <- extendrange(c(mv$bolls), f=0.05)
+
+## Evidence in favor of the underdispersion.
+xyplot(bolls[,"var"]~bolls[,"mean"], data=mv,
+       aspect="iso", xlim=xlim, ylim=ylim,
+       ylab="Sample variance", xlab="Sample mean")+
+    layer(panel.abline(a=0, b=1, lty=2))

man/defoliation.Rd

+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/legTools.R
+\docType{data}
+\name{defoliation}
+\alias{defoliation}
+\title{Bolls in cotton as function of artifitial defoliation}
+\format{a \code{data.frame} with 125 records and 4 variables.}
+\usage{
+data(defoliation)
+}
+\description{
+This dataset contais the result of a real experiment to
+    evaluate the effect of artifitial defoliation in combination with
+    phenological stage of occurence on the production of cotton
+    represented by the number of bolls produced at the end of the
+    crop cycle. The experiment is a \eqn{5\times 5} factorial with 5
+    replications casualized at random to the experimental units (a
+    randomized complete design). The experimental unit was a pot with
+    2 plants. An interesting fact about this data is that the
+    response is a count variable that shows underdispersion (sample
+    variance less than the sample mean).
+
+\itemize{
+\item \code{phenol} a categorical ordered factor with 5 levels
+    that represent the phenological stages of the cotton plant in
+    which defoliation was applied.
+\item \code{defol} a numeric factor with 5 levels that represents the
+    artifical level of defoliation (percent in leaf area removed with
+    scissors) applied for all leaves in the plant.
+\item \code{rept} index for each experimenal unit in each treatment cell.
+\item \code{bolls} the number of bolls produced (count variable)
+    evaluated at harvest.
+}
+}
+\details{
+The experiment was done in a greenhouse at Universidade
+    Federal da Grande Dourados. Visit
+\itemize{
+\item 1) \code{http://www.cabdirect.org/abstracts/20123299470.html}
+\item 2) \code{http://leg.ufpr.br/doku.php/publications:papercompanions:zeviani-jas2014}
+}
+1 for an article discussing the effect of defoliation on cotton yield and
+    visit 2 for an article that evaluate a count regression model able to
+    deal with the underdispersion. See the references section also.
+}
+\examples{
+library(lattice)
+library(latticeExtra)
+
+## x11(width=7, height=2.8)
+xyplot(bolls~defol|phenol, data=defoliation,
+       layout=c(NA, 1), type=c("p", "smooth"),
+       xlab="Artificial defoliation level",
+       ylab="Number of bolls produced",
+       xlim=extendrange(c(0:1), f=0.15), jitter.x=TRUE)
+
+## Sample mean and variance in each treatment cell.
+mv <- aggregate(bolls~phenol+defol, data=defoliation,
+                FUN=function(x) c(mean=mean(x), var=var(x)))
+str(mv)
+
+xlim <- ylim <- extendrange(c(mv$bolls), f=0.05)
+
+## Evidence in favor of the underdispersion.
+xyplot(bolls[,"var"]~bolls[,"mean"], data=mv,
+       aspect="iso", xlim=xlim, ylim=ylim,
+       ylab="Sample variance", xlab="Sample mean")+
+    layer(panel.abline(a=0, b=1, lty=2))
+}
+\references{
+Silva, A. M., Degrande, P. E., Suekane, R., Fernandes,
+    M. G., & Zeviani, W. M. (2012). Impacto de diferentes níveis de
+    desfolha artificial nos estádios fenológicos do
+    algodoeiro. Revista de Ciências Agrárias, 35(1), 163–172.
+
+Zeviani, W. M., Ribeiro, P. J., Bonat, W. H., Shimakura, S. E., &
+    Muniz, J. A. (2014). The Gamma-count distribution in the analysis
+    of experimental underdispersed data. Journal of Applied
+    Statistics, 41(12),
+    1–11. http://doi.org/10.1080/02664763.2014.922168
+}
+\keyword{datasets}
+

man/knit2wpCrayon.Rd

+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/knit2wpCrayon.R
+\name{knit2wpCrayon}
+\alias{knit2wpCrayon}
+\title{knit to wordpress that uses crayon sintax highlight}
+\usage{
+knit2wpCrayon(input, title = "A post from knitr", ..., action = c("newPost",
+  "editPost", "newPage"), postid, encoding = getOption("encoding"),
+  upload = FALSE, publish = FALSE, write = TRUE)
+}
+\arguments{
+\item{input}{a markdown or Rmarkdown file.}
+
+\item{title}{title for the post.}
+
+\item{...}{other meta information of the post. See}
+
+\item{action}{indicates a new post, a edition of the post or a new
+page.}
+
+\item{postid}{number of the post.}
+
+\item{encoding}{ht encoding of the input file.}
+
+\item{upload}{logical, if the file is to be updated to the blog.}
+
+\item{publish}{logical, if the post is to be published or stay in
+draft mode.}
+
+\item{write}{logical, if the result of knit should be written to a
+    html file. This is useful to copy from this file and paste inside
+    the Wordpress editor (on text mode, not visual mode).}
+}
+\value{
+Nothing is returned by the function.
+}
+\description{
+This function improves \code{RWordPress::knit2wp} to
+    allow properly render code when using Crayon Sintax Highlighter
+    in Wordpress.
+}
+\examples{
+\donttest{
+
+library(knitr)
+library(RWordPress)
+
+post <- "2015-08-24_polyGui.Rmd"
+title <- "Interface para regressão polinomial"
+categ <- c("gui", "rbloggers_pt")
+keywd <- c("gWdigets", "legTools", "lm", "poly")
+
+pass <- scan(n=1, what=character())
+options(WordpressLogin=c(walmes=pass),
+        WordpressURL="http://blog.leg.ufpr.br/xmlrpc.php")
+
+knit2wpCrayon(post, title=title,
+              action="editPost", postid=179,
+              categories=categ, mt_keywords=keywd,
+              ## write=TRUE, upload=FALSE,
+              write=FALSE, upload=TRUE,
+              publish=FALSE)
+
+}
+}
+\author{
+Walmes Zeviani, \email{walmes@ufpr.br}
+}
+

man/panel.segplot.by.Rd

+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/panel.segplot.by.R
+\name{panel.segplot.by}
+\alias{panel.segplot.by}
+\title{Lattice panel to non overlapping segments in \code{segplot()}}
+\usage{
+panel.segplot.by(x, y, z, data, centers, subscripts, groups, f = 0.05,
+  rev = FALSE, ...)
+}
+\arguments{
+\item{x,y,z,data,centers,subscripts,...}{see
+\code{\link[latticeExtra]{segplot}}.}
+
+\item{groups}{the grouping variable. Must be a factor.}
+
+\item{f}{numeric, factor that is the vertical distance among
+arrows. In general a value less than 1. Default is 0.05.}
+
+\item{rev}{logical, use the reverse order of the factor levels to
+    place the segments. Default is \code{FALSE}.}
+}
+\value{
+None is returned.
+}
+\description{
+This panel allows no overlapping of segments in
+    \code{latticeExtra::segplot()} when using the argument groups.
+}
+\examples{
+library(latticeExtra)
+
+m0 <- lm(log(breaks)~wool*tension, data=warpbreaks)
+anova(m0)
+par(mfrow=c(2,2)); plot(m0); layout(1)
+
+pred <- data.frame(wool=c("A", "B", "A", "B", "A", "B"),
+                   tension=c("L", "L", "M", "M", "H", "H"))
+
+X <- matrix(c(1, 1, 1, 1, 1, 1,
+              0, 1, 0, 1, 0, 1,
+              0, 0, 1, 1, 0, 0,
+              0, 0, 0, 0, 1, 1,
+              0, 0, 0, 1, 0, 0,
+              0, 0, 0, 0, 0, 1), nrow=6, ncol=6)
+
+## Estimate and standart error.
+## X\%*\%coef(m0)
+## sqrt(diag(X\%*\%vcov(m0)\%*\%t(X)))
+
+U <- chol(vcov(m0))
+pred$est <- X\%*\%coef(m0)
+pred$se <- sqrt(apply(X\%*\%t(U), MARGIN=1, FUN=function(x) sum(x^2)))
+
+tval <- qt(p=c(lwr=0.025, upr=0.975), df=df.residual(m0))
+pred <- cbind(pred, sweep(x=outer(pred$se, tval, "*"),
+                          MARGIN=1, STATS=pred$est, FUN="+"))
+
+## Overlapping segments.
+segplot(wool~lwr+upr, centers=est, data=pred, draw=FALSE)
+
+## Prefer ordering always before using "pch=".
+pred <- pred[with(pred, order(tension, wool)), ]
+
+segplot(tension~lwr+upr, data=pred,
+        centers=est, draw=FALSE,
+        ylab="Tension level",
+        xlab=expression("Estimate"\%+-\%"error margin for a 0.95 CI"),
+        groups=wool, f=0.05, rev=TRUE,
+        pch=as.integer(pred$wool),
+        panel=panel.segplot.by,
+        key=list(title="Type of wool", cex.title=1.1,
+                 text=list(levels(pred$wool)),
+                 lines=list(pch=1:2, lty=1),
+                 divide=1, type="o"))
+}
+\author{
+Walmes Zeviani, \email{walmes@ufpr.br}
+}
+\seealso{
+\code{\link[latticeExtra]{segplot}}
+}
+

man/plowing.Rd

@@ -6,20 +6,20 @@
 \title{Plowing level on corn yield}
 \format{a \code{data.frame} with 24 records and 3 variables.}
 \source{
-Frederico, P. (2009). Curso de Estatística Experimental
-(15th ed.). Piracicaba, São Paulo: FEALQ. (page 91)
+Frederico, P. (2009). Curso de Estatística Experimental (15th
+    ed.). Piracicaba, São Paulo: FEALQ. (page 91)
 }
 \usage{
 data(plowing)
 }
 \description{
 These data are from an experiment done by the engineer
-Duvilio Ometto to study the effect of plowing level on corn yield. It
-was used 2 levels of plowing: normal (or superficial) and deep. The
-experiment was done in a randomized complete block design with 6
-blocks. Corn yield (t/ha) was recorded in each experimental unit
-but in this experiment there was 2 experimental units for each factor
-level in each block.
+    Duvilio Ometto to study the effect of plowing level on corn
+    yield. It was used 2 levels of plowing: normal (or superficial)
+    and deep. The experiment was done in a randomized complete block
+    design with 6 blocks. Corn yield (t/ha) was recorded in each
+    experimental unit but in this experiment there was 2 experimental
+    units for each factor level in each block.
 
 \itemize{
     \item \code{block} a categorical unordered factor with 6 levels.

man/potatoyield.Rd

@@ -6,17 +6,17 @@
 \title{Potato variety competition experiment}
 \format{a \code{data.frame} with 32 records and 3 variables.}
 \source{
-Frederico, P. (2009). Curso de Estatística Experimental
-(15th ed.). Piracicaba, São Paulo: FEALQ. (page 76)
+Frederico, P. (2009). Curso de Estatística Experimental (15th
+    ed.). Piracicaba, São Paulo: FEALQ. (page 76)
 }
 \usage{
 data(potatoyield)
 }
 \description{
 These data are from an experiment done by the engineer
-Oscar A. Garay at Balcare, Argentina. The experiment was done in a
-randomized complete block design with 4 blocks. Potato yield (t/ha)
-was recorded in each experimental unit.
+    Oscar A. Garay at Balcare, Argentina. The experiment was done in
+    a randomized complete block design with 4 blocks. Potato yield
+    (t/ha) was recorded in each experimental unit.
 
 \itemize{
     \item \code{block} a categorical unordered factor with 4 levels.

man/wgpigs.Rd

@@ -6,8 +6,8 @@
 \title{Feeding type in pig weight gain}
 \format{a \code{data.frame} with 20 records and 2 variables.}
 \source{
-Frederico, P. (2009). Curso de Estatística Experimental
-(15th ed.). Piracicaba, São Paulo: FEALQ. (page 62)
+Frederico, P. (2009). Curso de Estatística Experimental (15th
+    ed.). Piracicaba, São Paulo: FEALQ. (page 62)
 }
 \usage{
 data(wgpigs)
@@ -15,10 +15,11 @@ data(wgpigs)
 \description{
 This is an artifial dataset corresponding a experiment
     to study the effect of feeding type (factor with 4 categorical
-nominal levels) in pig weight gain. The experiment was a randomized
-complete design with five experimental units per treatment level. The
-experimental unit was a pig. The response measured was weight gain
-from the beggining to the end of the experiment.
+    nominal levels) in pig weight gain. The experiment was a
+    randomized complete design with five experimental units per
+    treatment level. The experimental unit was a pig. The response
+    measured was weight gain from the beggining to the end of the
+    experiment.
 
 \itemize{
     \item \code{ft} feeding type, a categorical factor with 4

man/yscale.components.right.Rd

+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/yscale.components.right.R
+\name{yscale.components.right}
+\alias{yscale.component.right}
+\alias{yscale.components.right}
+\title{y-axis annotations on the right side}
+\source{
+When such feature was necessary, a search in the web was done
+    and a post in the r-help mailing list inspired us
+    \code{http://r.789695.n4.nabble.com/Spacing-between-lattice-panels-td855613.html}.
+}
+\usage{
+yscale.component.right(...)
+}
+\arguments{
+\item{...}{arguments passed by the lattice function called. See
+    \link[lattice]{yscale.components.default}.}
+}
+\description{
+This function if for place y axis annotation on the
+    right side of the plot.
+}
+\examples{
+library(lattice)
+library(latticeExtra)
+
+## alternating=2 works when relation="same".
+p1 <- xyplot(yield~K|N+P, data=npk,
+             scales=list(y=list(alternating=2)))
+useOuterStrips(p1)
+
+## y annotation don't is written on the right side.
+p2 <- xyplot(yield~K|N+P, data=npk,
+             scales=list(y=list(relation="free", alternating=2)))
+useOuterStrips(p2)
+
+## The desired result.
+p3 <- xyplot(yield~K|N+P, data=npk,
+             scales=list(y=list(relation="free", alternating=2)),
+             ylab=NULL, ylab.right="Yield",
+             yscale.component=yscale.component.right,
+             between=list(x=0.5, y=0.2),
+             par.settings=list(
+                 layout.widths=list(
+                     right.padding=-2,
+                     left.padding=-2,
+                     ylab.right=5),
+                 strip.background=list(col=c("gray50", "gray90"))),
+             )
+useOuterStrips(p3)
+}
+\author{
+Walmes Zeviani, \email{walmes@ufpr.br}
+}
+