Includes RData files and correspongin Rd files.

man/castorbeansYield.Rd

+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/legTools.R
+\docType{data}
+\name{castorbeansYield}
+\alias{castorbeansYield}
+\title{Castor beans variety competition experiments in some locations}
+\format{a \code{data.frame} with 45 records and 3 variables.}
+\source{
+Pimentel Gomes, F. (2009). Curso de Estatística Experimental
+    (15th ed.). Piracicaba, São Paulo: FEALQ. (page 149)
+
+Souza, O. Ferreira de.; Canecchio, F. V. (1952). Melhoramento de
+    mamoeira, VII. Bragantia 12:301-307.
+}
+\usage{
+data(castorbeansYield)
+}
+\description{
+These data are from a set of experiments evaluating
+    varieties of castor beans in terms of yield (kg/ha) for some
+    locations (counties).
+
+\itemize{
+
+\item \code{variety} a categorical unordered factor with 8 levels,
+    varieties and lines of castor beans.
+
+\item \code{loc} a categorical unordered factor with 5 levels, the
+    locations (counties) experimental stations.
+
+\item \code{meanYield} is the mean of yield for a variety in each
+    location. So, this the mean across all plots of the same variety
+    in each experiment.
+
+}
+}
+\details{
+The data in the book was not complete because doesn't report
+    individual plot values but the 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(castorbeansYield)
+str(castorbeansYield)
+
+xyplot(meanYield~variety, data=castorbeansYield,
+       groups=loc, type="o",
+       ylab=expression(Yield~(t~ha^{-1})),
+       xlab="Variety")
+}
+\keyword{datasets}
+

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/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}
+