R语言 spdep包 invIrM()函数中文帮助文档(中英文对照)

loveR

invIrM(spdep)
invIrM()所属R语言包：spdep

                                        Compute SAR generating operator
                                         计算SAR产生运营商

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Computes the matrix used for generating simultaneous autoregressive random variables, for a given value of rho, a neighbours list object, a chosen coding scheme style, and optionally a list of general weights corresponding to neighbours.
计算所使用的矩阵，用于产生同时自回归的随机变量，对于一个给定的值，rho沸石，一个邻居列表对象，编码方案选择样式，和任选的一般的权重对应的邻居列表。


用法----------Usage----------


invIrM(neighbours, rho, glist=NULL, style="W", method="solve",
feasible=NULL)
invIrW(listw, rho, method="solve", feasible=NULL)
powerWeights(W, rho, order=250, X, tol=.Machine$double.eps^(3/5))



参数----------Arguments----------

参数：neighbours
an object of class nb
一个对象的类nb


参数：rho
autoregressive parameter
自回归参数


参数：glist
list of general weights corresponding to neighbours
一般的权重对应的邻居列表


参数：style
style can take values W, B, C, and S
style可以采取的值W，B，C，和S的


参数：method
default solve, can also take value chol
默认情况下solve，也可以采取值chol


参数：feasible
if NULL, the given value of rho is checked to see if it lies within its feasible range, if TRUE, the test is not conducted
如果为NULL，给定值的Rho检查，看它是否是在可行范围内，如果是真的，测试进行


参数：listw
a listw object from for example nb2listw
一个listw的对象例如nb2listw


参数：W
A spatial weights matrix (either a dense matrix or a CsparseMatrix)
空间权重矩阵（无论是密集的矩阵或CsparseMatrix的）


参数：order
Power series maximum limit
电源系列最高限额


参数：X
A numerical matrix
一个数值矩阵


参数：tol
Tolerance for convergence of power series
幂级数的收敛公差


Details

详细信息----------Details----------

The invIrW function generates the full weights matrix V, checks that rho lies in its feasible range between 1/min(eigen(V)) and 1/max(eigen(V)), and returns the nxn inverted matrix
invIrW函数生成的全部权重矩阵V，支票，rho沸石是在其之间的可行范围1/min（本征（V））和1/max（本征（Ⅴ）），并返回nxn的逆矩阵

. With method=“chol”, Cholesky decomposition is used, thanks to contributed code by Markus Reder and Werner Mueller.
。使用方法=“哲”，Cholesky分解，这要归功于贡献的代码由马库斯·REDER的维尔纳·米勒。

The powerWeights function uses power series summation to cumulate the product
powerWeights功能使用幂级数求和来累积的产品

from
从

, which can be done by storing only sparse V and several matrices of the same dimensions as X. This makes it possible to handle larger spatial weights matrices.
，这可以通过只存储稀疏V和多个作为X的相同的尺寸，这使得能够处理较大的空间权重矩阵的矩阵。


值----------Value----------

An nxn matrix with a "call" attribute; the powerWeights function returns a matrix of the same dimensions as X which has been multipled by the power series equivalent of the dense matrix
nxn矩阵“呼叫”属性;powerWeights函数返回已乘以电源串联等效的密集矩阵的矩阵的相同的尺寸为X

.
。


（作者）----------Author(s)----------


Roger Bivand <a href="mailto:Roger.Bivand@nhh.no">Roger.Bivand@nhh.no</a>



参考文献----------References----------

<h3>See Also</h3>

实例----------Examples----------



nb7rt <- cell2nb(7, 7, torus=TRUE)
set.seed(1)
x <- matrix(rnorm(500*length(nb7rt)), nrow=length(nb7rt))
res0 <- apply(invIrM(nb7rt, rho=0.0, method="chol",
feasible=TRUE) %*% x, 2, function(x) var(x)/length(x))
res2 <- apply(invIrM(nb7rt, rho=0.2, method="chol",
feasible=TRUE) %*% x, 2, function(x) var(x)/length(x))
res4 <- apply(invIrM(nb7rt, rho=0.4, method="chol",
feasible=TRUE) %*% x, 2, function(x) var(x)/length(x))
res6 <- apply(invIrM(nb7rt, rho=0.6, method="chol",
feasible=TRUE) %*% x, 2, function(x) var(x)/length(x))
res8 <- apply(invIrM(nb7rt, rho=0.8, method="chol",
feasible=TRUE) %*% x, 2, function(x) var(x)/length(x))
res9 <- apply(invIrM(nb7rt, rho=0.9, method="chol",
feasible=TRUE) %*% x, 2, function(x) var(x)/length(x))
plot(density(res9), col="red", xlim=c(-0.01, max(density(res9)$x)),
  ylim=range(density(res0)$y),
  xlab="estimated variance of the mean",
  main=expression(paste("Effects of spatial autocorrelation for different ",
    rho, " values")))
lines(density(res0), col="black")
lines(density(res2), col="brown")
lines(density(res4), col="green")
lines(density(res6), col="orange")
lines(density(res8), col="pink")
legend(c(-0.02, 0.01), c(7, 25),
legend=c("0.0", "0.2", "0.4", "0.6", "0.8", "0.9"),
col=c("black", "brown", "green", "orange", "pink", "red"), lty=1, bty="n")
## Not run: [＃不运行：]
x <- matrix(rnorm(length(nb7rt)), ncol=1)
system.time(e <- invIrM(nb7rt, rho=0.9, method="chol", feasible=TRUE) %*% x)
system.time(e <- invIrM(nb7rt, rho=0.9, method="chol", feasible=NULL) %*% x)
system.time(e <- invIrM(nb7rt, rho=0.9, method="solve", feasible=TRUE) %*% x)
system.time(e <- invIrM(nb7rt, rho=0.9, method="solve", feasible=NULL) %*% x)
W <- as(as_dgRMatrix_listw(nb2listw(nb7rt)), "CsparseMatrix")
system.time(ee <- powerWeights(W, rho=0.9, X=x))
all.equal(e, as(ee, "matrix"), check.attributes=FALSE)
nb60rt <- cell2nb(60, 60, torus=TRUE)
W <- as(as_dgRMatrix_listw(nb2listw(nb60rt)), "CsparseMatrix")
set.seed(1)
x <- matrix(rnorm(dim(W)[1]), ncol=1)
system.time(ee <- powerWeights(W, rho=0.3, X=x))
str(as(ee, "matrix"))
obj <- errorsarlm(as(ee, "matrix")[,1] ~ 1, listw=nb2listw(nb60rt), method="Matrix")
coefficients(obj)

## End(Not run)[＃（不执行）]

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


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