我有一个包含lm公式的列的数据框。当我为特定行[[2]]运行此列时,我得到了该LM的摘要输出。这完全有效,但由于我在该列中有959行,我想写一个for循环,以便对这些回归做一个anova。如何指定我想在for循环中寻址该列表中的所有对象?
为了让您有一个很好的理解,这里有一个MWE:
数据帧:
structure(list(Week = 7:17, Category = c("2", "2", "2", "2",
"2", "2", "2", "2", "2", "2", "2"), Brand = c("3", "3", "3",
"3", "3", "3", "3", "3", "3", "3", "3"), Display = c(0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0), Sales = c(0, 0, 0, 0, 13.440948, 40.097397,
32.01384, 382.169189, 2830.748779, 4524.460938, 1053.590576),
Price = c(0, 0, 0, 0, 5.949999, 5.95, 5.950003, 4.87759,
3.787015, 3.205987, 4.898724), Distribution = c(0, 0, 0,
0, 1.394019, 1.386989, 1.621416, 8.209759, 8.552915, 9.692097,
9.445554), Advertising = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0), lnSales = c(11.4945151554497, 11.633214247508, 11.5862944141137,
11.5412559646132, 11.4811122484454, 11.4775106999991, 11.6333660772506,
11.4859819773102, 11.5232680456161, 11.5572670584292, 11.5303686934256
), IntrayearCycles = c(4.15446534315765, 3.62757053512638,
2.92387946552647, 2.14946414386239, 1.40455011205262, 0.768856938870769,
0.291497141953598, -0.0131078404184544, -0.162984144025091,
-0.200882782749248, -0.182877633924882), `Competitor Advertising` = c(10584.87063,
224846.3243, 90657.72553, 0, 0, 0, 2396.54212, 0, 0, 0, 40343.49444
), `Competitor Display` = c(0.385629, 2.108133, 2.515806,
4.918288, 3.81749, 3.035847, 2.463194, 3.242594, 1.850399,
1.751096, 1.337943), `Competitor Prices` = c(5.30989, 5.372752,
5.3717245, 5.3295525, 5.298393, 5.319466, 5.1958415, 5.2941095,
5.296757, 5.294059, 5.273578), ZeroSales = c(1, 1, 1, 1,
0, 0, 0, 0, 0, 0, 0)), .Names = c("Week", "Category", "Brand",
"Display", "Sales", "Price", "Distribution", "Advertising", "lnSales",
"IntrayearCycles", "Competitor Advertising", "Competitor Display",
"Competitor Prices", "ZeroSales"), row.names = 1255:1265, class = "data.frame")
然后我应用for循环来估计一个误差修正模型(使用ECM包) - 这会产生一个线性模型ouptut - 。这个for循环用于估计959个单独的回归。
f <- function(.) {
xeq <- as.data.frame(select(., lnPrice, lnAdvertising, lnDisplay, IntrayearCycles, lnCompetitorPrices, lnCompADV, lnCompDISP, ADVxDISP, ADVxCYC, DISPxCYC, ADVxDISPxCYC))
xtr <- as.data.frame(select(., lnPrice, lnAdvertising, lnDisplay, IntrayearCycles, lnCompetitorPrices, lnCompADV, lnCompDISP, ADVxDISP, ADVxCYC, DISPxCYC, ADVxDISPxCYC))
print(xeq)
print(xtr)
summary(ecm(.$lnSales, xeq, xtr, includeIntercept = TRUE))
}
Models <- DatasetThesisSynergyClean %>%
group_by(Category, Brand) %>%
do(Model = f(.))
要查看特定模型的摘要(此处为模型2),您可以解决:
Models$model[[2]]
因此,我想从此摘要输出中提取特定值。但首先我想提取残差平方和(RSS)来做一个anova。我为一个列表对象执行此操作,如下所示:
anova_output_Unitmodels <- anova(Models$Model[[2]])
RSS_Unit <- anova_output_Unitmodels$`Sum Sq`[nrow(anova_output_Unitmodels)] #saving the RSS
现在,我希望在所有列表对象中循环,从对象[[1]]到[[959]]。这个RSS输出必须保存到最后我需要总结所有这些RSS值。
此外,如果这有效,我需要从所有模型中提取所有变量的所有系数,t值和p值。然后我还需要解决列表中的特定对象并将$ coefficient放在其后面,但我也无法管理它。
以下是我实施@Roman Lustrik答案的方法。
extractRSS <- function(x) {
an <- anova(x)
RSS_Unit <- an$`Sum Sq`[nrow(an)]
return(RSS_Unit)
}
sapply(Model, FUN = extractRSS)
我也试过为一个特定的模型做这个,但这给了我一个错误:
SapplyRSS <- sapply(Models$Model, FUN = extractRSS)
我有另一个想法,并考虑以不同的方式循环它,但效果不好但它是一个开始:
如果你这样做
RSS2<- sum(Models$Model[[2]]$residuals^2)
所以我想在for循环中复制它:
for(i in residuals.lm){
AllRSS<- as.matrix(c(1:949))
AllRSS <- as.data.frame(AllRSS)
SumRSS <- sum(Models$Model[[i]]$residuals^2)
SumRSS <- as.data.frame(SumRSS)
TotalRSS <- cbind(SumRSS, AllRSS)}
TotalRSS <- SumRSS[NULL,]
它首先在for函数中指定i,我不知道这是否正确。最终它给我留下了一个空的数据框,或者一个具有相同品牌价值的数据框。
@MichaelChirico可能有这样的想法。
extractRSS <- function(x) {
an <- anova(x)
RSS_Unit <- an$`Sum Sq`[nrow(an)]
return(RSS_Unit)
}
sapply(Model, FUN = extractRSS)
sapply
将遍历每个Models$Model[[i]]
对象并提取RSS。您可以修改此功能以包含其他信息。结果可能会被强制转换为一些更简单的对象。你可以通过sapply(..., simplify = FALSE)
来防止这种情况。
另一种方法是将所有列表对象导出为数据框中的对象。你这样做是通过:
names(Models$Model) <- paste0("C", Models$Category, "B", Models$Brand)
list2env(Models$Model, .GlobalEnv)
然后我写了一个for循环来解决这些对象,并用for循环中的值反复填充空数据帧。具体如下:
for(X in c("0","1","3")){
EmptyRSS <- data.frame(RSS = 0)
ModelX <- get(paste0("C", X, "B2"))
RSS <- sum(ModelX$residuals^2)
RSS <- as.data.frame(RSS)
DF <- ModelX$df[2]
DF <- as.data.frame(DF)
RSSDF <- cbind(RSS, DF)
TotalRSS2 <- rbind(TotalRSS2, RSSDF)
}
TotalRSS2 <- RSSDF[NULL,]
您应该在循环外运行命令两次。