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zBWGQ<fB){nGrSe2j@`_ZIk5iVh6bbA_xOCxHpTfdX>)3MZkWbWCKNJxLECP@)A_ks K9`kb97#IL3ts(&c literal 0 HcmV?d00001 diff --git a/man/castorbeansYield.Rd b/man/castorbeansYield.Rd new file mode 100644 index 0000000..9aeb846 --- /dev/null +++ b/man/castorbeansYield.Rd @@ -0,0 +1,61 @@ +% 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} + diff --git a/man/peanutYield.Rd b/man/peanutYield.Rd new file mode 100644 index 0000000..5feba59 --- /dev/null +++ b/man/peanutYield.Rd @@ -0,0 +1,63 @@ +% 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} + diff --git a/man/peanutYield2.Rd b/man/peanutYield2.Rd new file mode 100644 index 0000000..ebd061c --- /dev/null +++ b/man/peanutYield2.Rd @@ -0,0 +1,60 @@ +% 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} + diff --git a/man/potatoYield2.Rd b/man/potatoYield2.Rd new file mode 100644 index 0000000..9dfc732 --- /dev/null +++ b/man/potatoYield2.Rd @@ -0,0 +1,65 @@ +% 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} + -- GitLab