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General improvements to be released on CRAN

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1 parent da40eea commit 944a50be6d0e1af57c655f2ea45d4fe2311a1e72 @jcfaria committed Jun 22, 2012
Showing with 89 additions and 58 deletions.
  1. +5 −0 ChangeLog
  2. +3 −3 DESCRIPTION
  3. +36 −21 man/TukeyC-package.Rd
  4. +13 −4 man/TukeyC.Rd
  5. +11 −5 man/TukeyC.nest.Rd
  6. +4 −6 man/make.TukeyC.groups.Rd
  7. +4 −9 man/make.TukeyC.test.Rd
  8. +5 −4 man/plot.TukeyC.Rd
  9. +2 −2 man/sorghum.Rd
  10. +6 −4 man/summary.Rd
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@@ -1,3 +1,8 @@
+2012-06-22 vs. 1.0-6 - Jose Claudio Faria <joseclaudio.faria@gmail.com>
+ * Ivan Bezerra Allaman has began to work in the project as co-author.
+ * Overall improvements were made in the documetantion.
+ * First version released on CRAN.
+
2012-05-27 vs. 1.0-5 - Jose Claudio Faria <joseclaudio.faria@gmail.com>
* Overall improvements were made in the demos, examples and documetantion
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@@ -1,9 +1,9 @@
Package: TukeyC
Type: Package
Title: Convencional Tukey Test
-Version: 1.0-5
-Date: 2012-05-27
-Author: Jose Claudio Faria & Enio Jelihovschi
+Version: 1.0-6
+Date: 2012-06-22
+Author: Jose Claudio Faria, Enio Jelihovschi and Ivan Bezerra Allaman
Maintainer: Jose Claudio Faria <joseclaudio.faria@gmail.com>
Depends: R (>= 2.6.0), base
Description: Perform the conventional Tukey test from aov and aov.list objects
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@@ -6,45 +6,60 @@
Conventional Tukey Test}
\description{
- This package perform the Tukey test in the conventional way,
- assigning letters for each group of means, for simple
- experimental designs and schemes. The most usual designs are:
+ This package performs what is known as the Tukey HSD test in the conventional
+ way. It also uses an algorithm which divides the set of all means in groups
+ and assigns letters to the different groups, allowing for overlapping. This is
+ done for simple experimental designs and schemes. The most usual designs are:
Completely Randomized Design (CRD),
- Randomized Complete Block Design (RCBD),
- Latin Squares Design (LSD);
- the most usual schemes are:
+ Randomized Complete Block Design (RCBD) and
+ Latin Squares Design (LSD).
+
+ The most usual schemes are:
Factorial Experiment (FE),
Split-Plot Experiment (SPE) and
Split-Split-Plot Experiment (SPE).
- Where it is aplicable, the package can be used for both (balanced or
- unbalanced) experiments.
+
+ The package can be used for both balanced or
+ unbalanced (when possible), experiments.
\R has some functions
(\code{\link[stats]{TukeyHSD}} provided by \code{stats},
\code{\link[multcomp]{glht}} provided by \code{multcomp},
\code{\link[agricolae]{HSD.test}} provided by \code{agricolae} and
- \code{\link[multcomp]{cld}} provided by \code{multcomp})
- allowing to perform the Tukey test. Some, for exemple \code{TukeyHSD},
- are concerned in the intervals based on the range of the
- sample means rather than the individual differences. The intervals returned
- by these functions are based on this Studentized range statistics.
+ \code{\link[multcomp]{cld}} provided by \code{multcomp}) which also performs
+ the Tukey test. The \code{TukeyHSD} returns intervals based on the range of the
+ sample means rather than the individual differences. Those intervals are based
+ on Studentized range statistics and are, in essence, confidence intervals.
This approach has two advantages: the p-value is showed allowing the user to
- flexibilize the inferencial decision and it is possible to plot the result of
- the test. But, has one disadvantage, the final result is more difficult to
- understand and summarize. Others (\code{glht}, \code{gcld}) are very usefful
- for experient statistical. Additionally, the majority of users of other
- statistical softwares are accustomed with letters grouping the means levels
- of the factor tested, making unattractive or difficult to adapt to the current
- aproach of \R.
+ flexibilize the inferencial decision and also make it possible to plot the
+ result of the test. However, it has one disadvantage, since the final result is
+ more difficult to understand and summarize. Others (\code{glht}, \code{cld})
+ are also useful but difficult to manage.
+ Additionally, most of users of other statistical softwares are very used with
+ letters grouping the means of the factor tested, making unattractive or
+ difficult to adapt to the current aproach of \R.
So, the main aim of this package is make available in \R environment the
conventional aproach of Tukey test with a set of flexible funtions and
S3 methods.}
+
+\references{
+ Miller, R.G. (1981) \emph{Simultaneous Statistical Inference}. Springer.
+
+ Ramalho M.A.P, Ferreira D.F, Oliveira A.C. (2000) \emph{Experimentacao em Genetica
+ e Melhoramento de Plantas}. Editora UFLA.
+
+ Steel, Torry & Dickey. (1997) \emph{Principles and procedures of statistics a
+ biometrical approach}. Third Edition.
+
+ Yandell, B.S. (1997) \emph{Practical Data Analysis for Designed Experiments}.
+ Chapman & Hall.}
\author{
Jose Claudio Faria (\email{joseclaudio.faria@gmail.com})\cr
- Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr}
+ Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr
+ Ivan Bezerra Allaman (\email{ivanalaman@gmail.com})}
\keyword{package}
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@@ -44,7 +44,7 @@
\item{sig.level}{Level of Significance used in the TukeyC algorithm to create
the groups of means. The default value is 0.05.}
\item{round}{Integer indicating the number of decimal places.}
- \item{\dots}{Potential further arguments (require by generic).} }
+ \item{\dots}{Potential further arguments (required by generic).} }
\details{
The function \code{TukeyC} returns an object of class \code{TukeyC}
@@ -65,11 +65,20 @@
\author{
Jose Claudio Faria (\email{joseclaudio.faria@gmail.com})\cr
- Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr}
+ Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr
+ Ivan Bezerra Allaman (\email{ivanalaman@gmail.com})}
\references{
- Ramalho MAP, Ferreira DF, Oliveira AC 2000. \emph{Experimentacao em Genetica
- e Melhoramento de Plantas}. Editora UFLA.}
+ Miller, R.G. (1981) \emph{Simultaneous Statistical Inference}. Springer.
+
+ Ramalho M.A.P, Ferreira D.F, Oliveira A.C. (2000) \emph{Experimentacao em Genetica
+ e Melhoramento de Plantas}. Editora UFLA.
+
+ Steel, Torry & Dickey. (1997) \emph{Principles and procedures of statistics a
+ biometrical approach}. Third Edition.
+
+ Yandell, B.S. (1997) \emph{Practical Data Analysis for Designed Experiments}.
+ Chapman & Hall.}
\examples{
##
View
@@ -53,7 +53,7 @@
\item{sig.level}{Level of Significance used in the TukeyC algorithm to create
the groups of means. The default value is 0.05.}
\item{round}{Integer indicating the number of decimal places.}
- \item{\dots}{Potential further arguments (require by generic).}}
+ \item{\dots}{Potential further arguments (required by generic).}}
\details{
The function \code{TukeyC.nest} returns an object of class
@@ -79,14 +79,20 @@
\author{
Jose Claudio Faria (\email{joseclaudio.faria@gmail.com})\cr
- Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr}
+ Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr
+ Ivan Bezerra Allaman (\email{ivanalaman@gmail.com})}
\references{
- Ramalho MAP, Ferreira DF, Oliveira AC 2000. \emph{Experimentacao em Genetica
+ Miller, R.G. (1981) \emph{Simultaneous Statistical Inference}. Springer.
+
+ Ramalho M.A.P, Ferreira D.F, Oliveira A.C. (2000) \emph{Experimentacao em Genetica
e Melhoramento de Plantas}. Editora UFLA.
- Scott RJ, Knott M 1974. A cluster analysis method for grouping mans in the
- analysis of variance. \emph{Biometrics}, \bold{30}, 507-512.}
+ Steel, Torry & Dickey. (1997) \emph{Principles and procedures of statistics a
+ biometrical approach}. Third Edition.
+
+ Yandell, B.S. (1997) \emph{Practical Data Analysis for Designed Experiments}.
+ Chapman & Hall.}
\examples{
##
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@@ -16,8 +16,8 @@
\emph{TRUE} or \emph{FALSE}, i.e, indicating whether or not equality
between the levels of factor.}}
-\details{
- ...}
+\details{ This function is an algorithm used to build up the groups of means,
+allowing for overlapping.}
\value{
The object returned by this function is a character matrix and the
@@ -30,9 +30,7 @@
\author{
Jose Claudio Faria (\email{joseclaudio.faria@gmail.com})\cr
- Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr}
-
-\seealso{
- ...}
+ Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr
+ Ivan Bezerra Allaman (\email{ivanalaman@gmail.com})}
\keyword{package}
View
@@ -22,7 +22,7 @@
\arguments{
\item{r}{A vector of the number of repicates of each level of the factor
being tested.}
- \item{MSE}{A vector of length 1 giving the hean squared error.}
+ \item{MSE}{A vector of length 1 giving the mean squared error.}
\item{m.inf}{A matrix of the levels of the factor being tested in
decreasing order.}
\item{ord}{A vector of ordered levels of the factor being tested.}
@@ -34,23 +34,18 @@
\item{mt}{The model table.}
\item{round}{Integer indicating the number of decimal places.}}
-\details{
- ...}
-
\value{
A list with 7 slots (\code{Table}, \code{Means}, \code{Result},
\code{Sig.Level}, \code{Diff_Prob}, \code{MSD} (The Minimum Significative
Difference) and \code{Replicates}) containing the most important results
of the test performed.}
\note{
- This function is mainly for internal use in the TukeyC package.}
+ This function is mainly for internal use in the TukeyC package.}
\author{
Jose Claudio Faria (\email{joseclaudio.faria@gmail.com})\cr
- Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr}
-
-\seealso{
- ...}
+ Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr
+ Ivan Bezerra Allaman (\email{ivanalaman@gmail.com})}
\keyword{package}
View
@@ -34,7 +34,7 @@
\item{col}{A vector of colors for the means representation.}
\item{xlab}{A label for the x axis.}
\item{ylab}{A label for the y axis.}
- \item{xlim}{The x limits of the plot}.
+ \item{xlim}{The x limits of the plot.}
\item{ylim}{The y limits of the plot.}
\item{id.lab}{Factor level names at x-axis.}
\item{id.las}{Factor level names written either horizontally or vertically.}
@@ -50,14 +50,15 @@
The \code{plot.TukeyC} function is a S3 method to plot \code{Tukey} and
\code{TukeyC.nest} objetcs. It generates a serie of points (the means) and a
vertical line showing the minimum e maximum of the values corresponding to
- each group mean. The groups are diferentiated by colors.}
+ each group mean.}
\author{
Jose Claudio Faria (\email{joseclaudio.faria@gmail.com})\cr
- Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr}
+ Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr
+ Ivan Bezerra Allaman (\email{ivanalaman@gmail.com})}
\references{
- Murrell, P. (2005) R Graphics. Chapman & Hall/CRC Press.}
+ Murrell, P. (2005) \emph{R Graphics}. Chapman & Hall/CRC Press.}
\seealso{\code{\link{plot}}}
View
@@ -26,8 +26,8 @@
(The Brazilian Agricultural Research Corporation, Corn and Sorghum section).}
\source{
-Ramalho, M.A.P. and Ferreira, D.F. and Oliveira, A.C. (2000).
-Experiment. em Gen. e Melhoramento de Plantas. Editora UFLA, Lavras,
+Ramalho, M.A.P. and Ferreira, D.F. and Oliveira, A.C. (2000)
+\emph{Experiment. em Gen. e Melhoramento de Plantas}. Editora UFLA, Lavras,
Brazil, page 167.}
\keyword{datasets}
View
@@ -13,15 +13,17 @@
\arguments{
\item{object}{A given object of the class \code{TukeyC}.}
- \item{complete}{A logical value indicating if the summary is complete (mean difference and p-value) or only the groups.}
- \item{\dots}{Potential further arguments (require by generic).}}
+ \item{complete}{A logical value indicating if the summary is complete (mean
+ difference and p-value) or only the groups.}
+ \item{\dots}{Potential further arguments (required by generic).}}
\author{
Jose Claudio Faria (\email{joseclaudio.faria@gmail.com})\cr
- Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr}
+ Enio Jelihovschi (\email{eniojelihovs@gmail.com})\cr
+ Ivan Bezerra Allaman (\email{ivanalaman@gmail.com})}
\references{
- Chambers, J. M. and Hastie, T. J. (1992) Statistical Models in S.
+ Chambers, J.M. and Hastie, T.J. (1992) \emph{Statistical Models in S}.
Wadsworth & Brooks/Cole.}
\seealso{\code{\link{TukeyC}}}

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