我对下面显示的空间回归代码有一个问题（代码示例）。运行回归后，我得到以下错误
Error in listw %*% as.matrix(ywithin) :
Cholmod error 'X and/or Y have wrong dimensions' at file ../MatrixOps/cholmod_sdmult.c, line 90
当我从回归中删除空间维度时，回归运行完美，所以我猜错误可能在空间权重矩阵中。有人可以帮我解决发生此错误的原因并推荐解决方案吗？
使用shapefile和数据链接到该文件夹： https://drive.google.com/drive/folders/1PFAhCpYnDCtV36DuTLh4V79Bs3RO5ESy?usp=sharing
requiredPackages <-
c("rio", "plm", "splm", "tmaptools", "spdep", "fields", "readxl")
ipak <- function(pkg) {
new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
if (length(new.pkg))
install.packages(new.pkg, dependencies = TRUE)
sapply(pkg, require, character.only = TRUE)
}
ipak(requiredPackages)
# URL's obtained from Google Shared Directory
pShareDataURL = "https://drive.google.com/open?id=1PjDlLiA99-3xuGPhPLltRg8uod6zPAKn" ## data1.xlsx
sShareDataURL = "https://drive.google.com/open?id=1VJGL8aSJomvWCnw9FPEWTJsQ65StYdzW" ## nuts2ashp
## strip "open?" and replace with us?export=download&
pdataURL <- gsub("open\\?", "uc\\?export=download\\&", pShareDataURL )
sdataURL <- gsub("open\\?", "uc\\?export=download\\&", sShareDataURL )
pdataDest = file.path("./data/data1.xlsx" )
sdataDest = file.path("./data/nuts2a.shp" )
if (!dir.exists("./data")) {
dir.create(file.path("./data"), showWarnings = FALSE)
}
# Download files
download.file(pdataURL, destfile = pdataDest, method = "wget", mode = "wb")
download.file(sdataURL, destfile = sdataDest, method = "wget", mode = "wb")
pdata <- read_excel(pdataDest)
shape_nuts <- read_shape(sdataDest)
shape_nuts <- shape_nuts[order(shape_nuts@data$NUTS_ID), ]
shape_nuts2 <-
shape_nuts[substr(shape_nuts@data$NUTS_ID, 1, 3) != "FR9" &
shape_nuts@data$NUTS_ID != "UKI1"
&
shape_nuts@data$NUTS_ID != "EL21" &
shape_nuts@data$NUTS_ID != "RO21", ]
#######computing the spatial weight matrix###########
coords2 <- coordinates(shape_nuts2) # getting coordinates of the polygon centroids
dm <- rdist.earth(coords2, miles = FALSE) # calculating distance between the polygon centroids
rownames(dm) <- shape_nuts2@data$NUTS_ID # naming the rows
colnames(dm) <- shape_nuts2@data$NUTS_ID # naming the columns
for (i in 1:dim(dm)[1]) {
dm[i, i] = 0
} # renders exactly zero all diagonal elements
dm1 <- ifelse(dm != 0, 1 / dm, dm) #inverting distance
# create a (normalized) listw object
dm1.lw <- mat2listw(dm1,
style = "W",
row.names = shape_nuts2@data$NUTS_ID)
#########regressions#######
spgr01 <- spgm(
rgrowthpc ~ lrgdp0pc + lefpayr,
data = pdata,
listw = dm1.lw,
model = "within",
lag = TRUE,
spatial.error = TRUE,
endog = ~ lefpayr,
instruments = ~ area_prop,
method = "w2sls"
)
> #########regressions#######
>
> spgr01 <- spgm(
+ rgrowthpc ~ lrgdp0pc + lefpayr,
+ data = pdata,
+ listw = dm1.lw,
+ model = "within",
+ lag = TRUE,
+ spatial.error = TRUE,
+ endog = ~ lefpayr,
+ instruments = ~ area_prop,
+ method = "w2sls"
+ )
Error in listw %*% as.matrix(ywithin) :
Cholmod error 'X and/or Y have wrong dimensions' at file ../MatrixOps/cholmod_sdmult.c, line 90
>
答案 0 :(得分：4)
在不知道你如何计算pdata的情况下，我们只能猜测。
如果您没有更改原始数据中的任何内容（如编辑@Technophobe01后的代码中所示），则会出现错误，因为在面板数据中，两个第一列应包含个人和时间索引，按此顺序。来自splm vignette：
在splm中输入数据集确实有三种可能性：
•包含单个索引的data.frame（作为其第一个变量） 和时间指数（第二个变量）。索引参数应该是 保留其默认值NULL
•data.frame和由要用作的空间和变量名称组成的字符向量 时间）指数
•pdata.frame类的对象。
因此，我们可以将pdata加载为：
library(gsheet)
url <- 'drive.google.com/file/d/1PjDlLiA99-3xuGPhPLltRg8uod6zPAKn'
pdata <- gsheet2tbl(url)
# reverse first and second column order
pdata <- pdata[, c(2:1,3:ncol(pdata))]
head(pdata)
# A tibble: 6 x 19
# nuts year d06 d13 eu10 d04 d09 eu2 eupigs eu12 lefpayr lrgdp0pc rgrowthpc lpopgr linvr wgipca area_prop laggdp0pc2 regid
# <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#1 AT11 1996 0 0 0 0 0 0 0 0 -5.01 4.19 0.0316 -1.30 -0.598 -2.18 0.243 4.21 1
#2 AT11 1997 0 0 0 0 0 0 0 0 -5.06 4.21 0.0498 -1.31 -0.609 -2.03 0.243 4.18 1
#3 AT11 1998 0 0 0 0 0 0 0 0 -5.11 4.24 0.0554 -1.31 -0.622 -1.87 0.245 4.19 1
#4 AT11 1999 0 0 0 0 0 0 0 0 -5.14 4.25 0.0314 -1.32 -0.629 1.71 0.253 4.21 1
#5 AT11 2000 0 0 0 1 0 0 0 0 -5.23 4.27 0.0546 -1.40 -0.562 -1.94 0.253 4.24 1
#6 AT11 2001 0 0 0 1 0 0 0 0 -5.30 4.28 0.0139 -1.30 -0.554 -2.18 0.271 4.25 1
然后您可以运行模型（假设为listw = dm1.lw并删除endog = ~lefpayr，因为您无法定义模型中已有的其他内生变量）：
spgr01 <- spgm(rgrowthpc ~ lrgdp0pc + lefpayr,
data = pdata,
listw = dm1.lw,
model = "within",
lag = TRUE,
spatial.error = TRUE,
instruments = ~area_prop,
method = "w2sls"
)
summary(spgr01)
#Spatial panel fixed effects GM model
#
#
#Call:
#spgm(formula = rgrowthpc ~ lrgdp0pc + lefpayr, data = pdata,
# listw = dm1.lw, model = "within", lag = TRUE, spatial.error = TRUE,
# instruments = ~area_prop, method = "w2sls")
#
#Residuals:
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# -1.087 -0.934 -0.908 -0.888 -0.861 -0.421
#
#Estimated spatial coefficient, variance components and theta:
# Estimate
#rho 0.84261722
#sigma^2_v 0.00084123
#
#Spatial autoregressive coefficient:
# Estimate Std. Error t-value Pr(>|t|)
#lambda 1.84215 0.26141 7.0469 1.83e-12 ***
#
#Coefficients:
# Estimate Std. Error t-value Pr(>|t|)
#lrgdp0pc 0.20412808 0.01637557 12.4654 < 2.2e-16 ***
#lefpayr -0.00080159 0.00022879 -3.5036 0.0004591 ***
#---
#Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1