fish(rrcov)
fish()所属R语言包：rrcov
Fish Catch Data Set
渔获量数据集
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The Fish Catch data set contains measurements on 159 fish caught in the lake Laengelmavesi, Finland.
渔获量数据集包含159捕获的鱼在的湖Laengelmavesi的，芬兰的测量。
用法----------Usage----------
data(fish)
格式----------Format----------
A data frame with 159 observations on the following 7 variables.
159以下7个变量的观察与数据框。
Weight Weight of the fish (in grams)
Weight的鱼的重量（以克计）
Length1 Length from the nose to the beginning of the tail (in cm)
Length1长度从鼻子到尾巴开始（厘米）
Length2 Length from the nose to the notch of the tail (in cm)
Length2从鼻子到尾巴的缺口长度（厘米）
Length3 Length from the nose to the end of the tail (in cm)
Length3从鼻子到尾巴末端的长度（厘米）
Height Maximal height as % of Length3
Height最大高度，长度3％
Width Maximal width as % of Length3
Width的最大宽度为长度3％的
Species Species
Species物种
Details
详细信息----------Details----------
The Fish Catch data set contains measurements on 159 fish caught in the lake Laengelmavesi, Finland. For the 159 fishes of 7 species the weight, length, height, and width were measured. Three different length measurements are recorded: from the nose of the fish to the beginning of its tail, from the nose to the notch of its tail and from the nose to the end of its tail. The height and width are calculated as percentages of the third length variable. This results in 6 observed variables, Weight, Length1, Length2, Length3, Height, Width. Observation 14 has a missing value in variable Weight, therefore this observation is usually excluded from the analysis. The last variable, Species, represents the grouping structure: the 7 species are 1=Bream, 2=Whitewish, 3=Roach, 4=Parkki, 5=Smelt, 6=Pike, 7=Perch. This data set was also analyzed in the context of robust Linear Discriminant Analysis by Todorov (2007), Todorov and Pires (2007).
渔获量数据集包含159捕获的鱼在的湖Laengelmavesi的，芬兰的测量。为159的7种鱼类的重量，长度，高度和宽度进行了测量。三种不同的长度测量记录：从鼻子里的鱼，它的尾巴开始，从鼻子到其尾部的凹槽中，从鼻子到它的尾巴。作为第三个长度的变量的百分比计算的高度和宽度。这样的结果在6个观测变量，重量，长度，长度2，长度3，高度，宽度。观察14有缺失值在变量的重量，因此，这种观测通常是从分析中排除。最后一个变量，物种的分组结构：7种，团头鲂，1 = 2 = Whitewish，3，4 = 5 =冶炼，6 Parkki，罗奇派克，7 =鲈鱼。托多罗夫（2007年），托多罗夫和皮雷（2007年）的背景下，强大的线性判别分析，该数据集进行了分析。
源----------Source----------
Journal of Statistical Education, Fish Catch Data Set, [http://www.amstat.org/publications/jse/datasets/fishcatch.txt] accessed August, 2006.
[统计教育，渔获量数据集，http://www.amstat.org/publications/jse/datasets/fishcatch.txt]访问2006年8月。
参考文献----------References----------
discriminant analysis, Statistical Methods and Applications, 15, 395–407, doi:10.1007/s10260-006-0032-6.
linear discriminant analysis methods, REVSTAT Statistical Journal, 5, 63–83.
实例----------Examples----------
data(fish)
# remove observation #14 containing missing value[删除观察第14含缺失值]
fish <- fish[-14,]
# The height and width are calculated as percentages [的高度和宽度的百分比计算]
# of the third length variable[第三个长度可变]
fish[,5] <- fish[,5]*fish[,4]/100
fish[,6] <- fish[,6]*fish[,4]/100
# plot a matrix of scatterplots[绘制散点图矩阵]
pairs(fish[1:6],
main="Fish Catch Data",
pch=21,
bg=c("red", "green3", "blue", "yellow", "magenta", "violet", "turquoise")[unclass(fish$Species)])
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-28 20:46:00
