bartlett.test(formula, data) formula:公式的格式,由数值和组别组成,如value ～ group data:一个矩阵或数据框 该函数返回值(输出值)包含以下内容: statistic:Bartlett的K平方检验统计量 parameter:检验统计量的近似卡方分布的自由度。 p.value:检验的p值 3.3.1 具有一个自变量的Bartlett检验: 研究问题是:检验三组...
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> p=ggplot(data=longdata,aes(x=Ozone,y=value,color=factor (Month))) > p+geom_point(shape=20,size=4)+facet_wrap(~variable,scales="free_y")+geom_smooth(aes(group=1),fill="gray80") 和stack()一样,melt()也有对应的函数用来还原数据:acast()用于数组,dcast()用于数据框,其中的参数formula...
BP = 12.718, df = 9, p-value = 0.1758 library(car);library(carData) ncvTest(lmfit) Non-constant Variance Score Test Variance formula: ~ fitted.values Chisquare = 0.0005196456, Df = 1, p = 0.98181 olsrr 包也提供了4种异方差检验Bartlett Test、Breusch Pagan Test、Score Test、F Test,...
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gather(tdata,key='key',value='value',2:4) Spread函数则是将合并数据转化成tidyr形式的数据 例如,对之前合并的tdata函数进行分开: gdata<-gather(tdata,key='key',value='value',2:4)spread(gdata,key='key',value="value") 就可以还原数据: ...
optim(c(0,0),<func>)——优化问题函数,c(0,0)是优化函数参数的初始值,返回值par是参数最优点值,value是参数的最优点时平方误差值,counts是返回执行输入函数func的次数以及梯度gradient的次数,convergence值为0表示有把握找到最优点,非0值时对应错误,message是一些其它信息。
value.name="hp") df.l$No<-factor(df.l$No) str(df.l) ## 'data.frame': 75 obs. of 4 variables: ## $ No : Factor w/ 15 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ... ## $ group: Factor w/ 3 levels "A","B","C": 1 1 1 1 1 2 2 2 2 ...
4、检验解释变量x与目标变量y之间存在的依赖关系,统计量F,用p-value值,p值越小越好 5、绘图检验plot(<lm>)——绘制线性模型,和qq.plot误差的正态QQ图 6、精简线性模型,向后消元法 线性回归模型基础 lm(formula=x~y,data,subset)——回归分析,x是因变量(响应变量),y是自变量(指示变量),formular=y~x是...