Merge branch 'issue#11' into 'devel'

Issue#11: Datasets of the chapter 8

This branch brings
  - Datasets of the chapter 8. So, 5 data frames are included with the corresponding `data-raw/*.R` and `data/*.RData` files and documentation on the `R/legTools.R`;
  - @brunaw is included as a collaborator in the DESCRIPTION;

See merge request !13

man/filterCake.Rd

@@ -19,13 +19,18 @@ These data are from an \eqn{2^2} factorial experiment
     fertilization.
 
 \itemize{
+
 \item \code{block} a factor with 4 levels.
+
 \item \code{mineral} low (-1) and high (+1) levels of mineral
     fertilization.
-  \item \code{cake} low (-1) and high (+1) levels of fetilization
-    with filter cake.
-  \item \code{y} some response variable. The text book doesn't give
-    any information.
+
+\item \code{cake} low (-1) and high (+1) levels of fetilization with
+    filter cake.
+
+\item \code{y} some response variable. The text book doesn't give any
+    information.
+
 }
 }
 \examples{

man/mangoAcidity.Rd

@@ -21,11 +21,16 @@ These data are from an observational study along 3 years
     Novermber, December and January.
 
 \itemize{
+
 \item \code{variety} a categorical variable with 6 levels that
     represents mango varieties studied.
+
 \item \code{year} the year of harvesting.
+
 \item \code{month} the month of harvesting.
+
 \item \code{acid} mean of the acidity determined in 3 fruits.
+
 }
 }
 \examples{

man/peanutYield.Rd

+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/legTools.R
+\docType{data}
+\name{peanutYield}
+\alias{peanutYield}
+\title{Peanut variety competition experiments in some locations and
+    years}
+\format{a \code{data.frame} with 36 records and 4 variables.}
+\source{
+Pimentel Gomes, F. (2009). Curso de Estatística Experimental
+    (15th ed.). Piracicaba, São Paulo: FEALQ. (page 150)
+
+Souza, O. Ferreira de.; Abramides, Eduardo. (1952). Ensaios de
+    variedades de amendoim. Bragantia 12:349-358.
+}
+\usage{
+data(peanutYield)
+}
+\description{
+These data are from a set of experiments evaluating
+    varieties of peanut in terms of yield (kg/ha) for some locations
+    and years.
+
+\itemize{
+
+\item \code{variety} a categorical unordered factor with 4 levels,
+    peanut varieties.
+
+\item \code{loc} a categorical unordered factor with 3 levels, the
+    locations (counties) of the experimental stations.
+
+\item \code{year} a categorical factor, the crop year.
+
+\item \code{meanYield} is the adjusted mean of yield for a variety in
+    each location and year.
+
+}
+}
+\details{
+The data in the book was not complete because doesn't report
+    individual plot values but the adjusted mean for a variety in
+    each single experiment. Neither mention which experimental design
+    was used in each station. The book report the Mean Square Error
+    estimates for each experiment. These values as provided as an
+    attribute of the object, \code{attr(peanut, "MSE")} and they
+    comes from the ANOVA table corresponding to an appropriate model
+    for each location. With these MSE is possible use them in a such
+    a way that a partial ANOVA table can be obtained to test the
+    effect of location, variety and its interaction.
+}
+\examples{
+require(lattice)
+
+data(peanutYield)
+str(peanutYield)
+
+xyplot(meanYield~variety|year, data=peanutYield,
+       groups=loc, type="o",
+       ylab=expression(Yield~(t~ha^{-1})),
+       xlab="Variety")
+}
+\keyword{datasets}
+

man/peanutYield2.Rd

+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/legTools.R
+\docType{data}
+\name{peanutYield2}
+\alias{peanutYield2}
+\title{Peanut variety competition experiments in some locations}
+\format{a \code{data.frame} with 16 records and 3 variables.}
+\source{
+Pimentel Gomes, F. (2009). Curso de Estatística Experimental
+    (15th ed.). Piracicaba, São Paulo: FEALQ. (page 150)
+
+Souza, O. Ferreira de.; Abramides, Eduardo. (1952). Ensaios de
+    variedades de amendoim. Bragantia 12:349-358.
+}
+\usage{
+data(peanutYield2)
+}
+\description{
+These data are from a set of experiments evaluating
+    varieties of peanut in terms of yield (kg/ha) for some locations
+    in different years.
+
+\itemize{
+
+\item \code{variety} a categorical unordered factor with 4 levels,
+    peanut varieties.
+
+\item \code{loc} a categorical unordered factor with 4 levels, the
+    location:year of the experiment.
+
+\item \code{meanYield} is mean of yield for a variety in each
+    location:year.
+
+}
+}
+\details{
+The data in the book was not complete because doesn't report
+    individual plot values but the adjusted mean for a variety in
+    each single experiment. Neither mention which experimental design
+    was used in each station. The book report the Mean Square Error
+    estimates for each experiment. These values as provided as an
+    attribute of the object, \code{attr(peanut, "MSE")} and they
+    comes from the ANOVA table corresponding to an appropriate model
+    for each location. With these MSE is possible use them in a such
+    a way that a partial ANOVA table can be obtained to test the
+    effect of location, variety and its interaction.
+}
+\examples{
+require(lattice)
+
+data(peanutYield2)
+str(peanutYield2)
+
+xyplot(meanYield~variety, data=peanutYield2,
+       groups=loc, type="o",
+       ylab=expression(Yield~(t~ha^{-1})),
+       xlab="Variety")
+}
+\keyword{datasets}
+

man/plowing.Rd

@@ -22,9 +22,13 @@ These data are from an experiment done by the engineer
     units for each factor level in each block.
 
 \itemize{
+
 \item \code{block} a categorical unordered factor with 6 levels.
+
 \item \code{plow} a categorical unordered factor with 2 levels.
+
 \item \code{yield} corn yield (kg in 200 m\eqn{^2} of area).
+
 }
 }
 \examples{

man/potatoYield.Rd

@@ -19,10 +19,13 @@ These data are from an experiment done by the engineer
     (t/ha) was recorded in each experimental unit.
 
 \itemize{
+
 \item \code{block} a categorical unordered factor with 4 levels.
-    \item \code{variety} a categorical unordered factor with 8
-    levels.
+
+\item \code{variety} a categorical unordered factor with 8 levels.
+
 \item \code{yield} potato yield (t/ha).
+
 }
 }
 \examples{

man/potatoYield2.Rd

+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/legTools.R
+\docType{data}
+\name{potatoYield2}
+\alias{potatoYield2}
+\title{Potato variety competition experiments in several locations}
+\format{a \code{data.frame} with 56 records and 3 variables. There is
+    an attribute named \code{MSE}, a named vector containing the Mean
+    Squares Errors estimates for each experiment.}
+\source{
+Pimentel Gomes, F. (2009). Curso de Estatística Experimental
+    (15th ed.). Piracicaba, São Paulo: FEALQ. (page 147)
+}
+\usage{
+data(potatoYield2)
+}
+\description{
+These data are from a set of experiments done by the
+    engineer Oscar A. Garay at Balcare, Argentina. These experiments
+    were done in a randomized complete block design with 4 blocks and
+    at 7 locations on the potato production region at the Buenos
+    Aires province.
+
+\itemize{
+
+\item \code{variety} a categorical unordered factor with 8 levels,
+    varieties of potato.
+
+\item \code{loc} a categorical unordered factor with 7 levels, the
+    locations that represent farms or experimental stations.
+
+\item \code{sumYield} is the sum of yield for a variety in each
+    experiment. Then, this sum values across 4 blocks in each
+    experiment. To get the mean yield you should divide by 4. Yield
+    is t/ha.
+
+}
+}
+\details{
+The data in the book was not complete because doesn't report
+    individual plot values but, instead, the sum for a variety in
+    each experiment. To do a joint or global analysis, with all
+    locations, varieties and blocks, its necessary all individual
+    plot values. The book report the Mean Square Error estimates for
+    each experiment as an attribute of the object,
+    \code{attr(potatoYield2, "MSE")} and they comes from the ANOVA
+    table in which the model is \code{~block+variety} for each
+    location. The data set \link[legTools]{potatoYield} correspond
+    the location 3. With these MSE is possible use them in a such a
+    way that a partial ANOVA table can be obtained to test the effect
+    of location, variety and its interaction.
+}
+\examples{
+require(lattice)
+
+data(potatoYield2)
+str(potatoYield2)
+
+xyplot(sumYield/4~variety, data=potatoYield2,
+       groups=loc, type="o",
+       ylab=expression(Yield~(t~ha^{-1})),
+       xlab="Variety")
+}
+\keyword{datasets}
+

man/sugarcaneYield.Rd

@@ -19,10 +19,13 @@ These data are from an experiment done by The West São
     (kg/plot) was recorded in each experimental unit.
 
 \itemize{
+
 \item \code{block} a categorical unordered factor with 4 levels.
-    \item \code{variety} a categorical unordered factor with 7
-    levels.
+
+\item \code{variety} a categorical unordered factor with 7 levels.
+
 \item \code{yield} sugarcane yield (kg/plot).
+
 }
 }
 \examples{

man/sugarcaneYield2.Rd

@@ -18,14 +18,18 @@ These data are from an experiment done in a latin square
     experimental unit.
 
 \itemize{
-    \item \code{row} the rows of the latin square that controls in
-    one dimention. A categorical unordered factor with 5 levels.
-    \item \code{col} the columns of the latin square that controls in
-    one dimention perpendicular to the previus. A categorical
-    unordered factor with 5 levels.
-    \item \code{variety} a categorical unordered factor with 5
-    levels.
+
+\item \code{row} the rows of the latin square that controls in one
+    dimention. A categorical unordered factor with 5 levels.
+
+\item \code{col} the columns of the latin square that controls in one
+    dimention perpendicular to the previus. A categorical unordered
+    factor with 5 levels.
+
+\item \code{variety} a categorical unordered factor with 5 levels.
+
 \item \code{yield} sugarcane yield (kg/plot).
+
 }
 }
 \examples{

man/sugarcaneYield3.Rd

@@ -18,16 +18,21 @@ These data are from an experiment done in a latin square
     experimental unit.
 
 \itemize{
-  \item \code{row} the rows of the latin square that controls in
-    one dimention. A categorical unordered factor with 6 levels.
-  \item \code{col} the columns of the latin square that controls in
-    one dimention perpendicular to the previus. A categorical
-    unordered factor with 6 levels.
-  \item \code{fertil} a categorical unordered factor with 6
-    levels that is the fertilization strategy applied. These levels
-    are a result of treatment cells in a three incomplete factorial
+
+\item \code{row} the rows of the latin square that controls in one
+    dimention. A categorical unordered factor with 6 levels.
+
+\item \code{col} the columns of the latin square that controls in one
+    dimention perpendicular to the previus. A categorical unordered
+    factor with 6 levels.
+
+\item \code{fertil} a categorical unordered factor with 6 levels that
+    is the fertilization strategy applied. These levels are a result
+    of treatment cells in a three incomplete factorial
     arrangrment. See detais for more information.
+
 \item \code{yield} sugarcane yield (kg/plot).
+
 }
 }
 \details{
@@ -58,7 +63,8 @@ levelplot(yield~row+col,
               colors=brewer.pal(n=11, name="Spectral")))+
     layer(with(sugarcaneYield3,
                panel.text(x=row, y=col,
-                          label=sprintf("\%s\\n\%0.2f", fertil, yield))))
+                          label=sprintf("\%s\\n\%0.2f",
+                                        fertil, yield))))
 
 aggregate(yield~row, data=sugarcaneYield3, FUN=mean)
 aggregate(yield~col, data=sugarcaneYield3, FUN=mean)

man/sugarcaneYield4.Rd

@@ -17,12 +17,19 @@ These data are from an \eqn{3^3} factorial experiment
     studing the effect of NPK on the yield of sugar cane.
 
 \itemize{
+
   \item \code{block} a local control factor with 3 levels.
+
   \item \code{rept} factor with 2 levels.
+
   \item \code{N} integer coded nitrogen levels (0, 1, 2).
+
   \item \code{P} integer coded phosphorus levels (0, 1, 2).
+
   \item \code{K} integer coded potassium levels (0, 1, 2).
+
   \item \code{yield} sugar cane yield (ton/ha).
+
 }
 }
 \details{

man/vinasseFert.Rd

@@ -19,13 +19,18 @@ These data are from an \eqn{2^2} factorial experiment
     fertilization.
 
 \itemize{
+
 \item \code{block} a factor with 4 levels.
+
 \item \code{mineral} low (-1) and high (+1) levels of mineral
     fertilization.
+
 \item \code{vinasse} low (-1) and high (+1) levels of fetilization
    with vinasse.
-  \item \code{y} some response variable. The text book doesn't give
-    any information.
+
+\item \code{y} some response variable. The text book doesn't give any
+    information.
+
 }
 }
 \examples{

man/wgPigs.Rd

@@ -13,18 +13,20 @@ Pimentel Gomes, F. (2009). Curso de Estatística Experimental
 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
+This is an artificial data set 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
+    measured was weight gain from the beginning to the end of the
     experiment.
 
 \itemize{
-    \item \code{ft} feeding type, a categorical factor with 4
-    levels.
+
+\item \code{ft} feeding type, a categorical factor with 4 levels.
+
 \item \code{wg} weight gain (kg).
+
 }
 }
 \examples{

man/wgPigs2.Rd

@@ -22,15 +22,20 @@ This is an artifial dataset corresponding a experiment
     experiment.
 
 \itemize{
+
 \item \code{litter} a categorical factor with 4 levels that
     represents the rows of the lattin square design and control for
     the differences among litters.
+
 \item code{size} a categorical ordered variable that represents the
     columns of latin square desing and control for the weight of the
     animals at the beggining of the experiment.
+
 \item \code{age} age of the animal (days) when castration was
     done. \code{controls} are the animals without castration.
+
 \item \code{wg} weight gain (kg) after 252 days.
+
 }
 }
 \examples{