Hello All:



I am working on parcel-level housing dataset to estimate the impact of
various variables on home sale prices (N is approx. 90,000).

I created the spatial weight metrics using sale year of four nearest houses
to assign weights.  Next, I ran LM tests and the spatial lag and error
models using spdep package.

I get the following error message when I try to run spatial lag or error
models using the method "eigen".
Error in matrix(0, nrow = n, ncol = n) : too many elements specified

The code is:
> fecurrentcombinedlag <-lagsarlm(fecurrentcombined, data = spssall,
lw_test2.csv, na.action=na.fail, type="lag", method="eigen", quiet=TRUE,
zero.policy=FALSE, interval = c(-1, 0.999), tol.solve=1.0e-20)



Since the dataset is large, I replaced "eigen" with "LU" or "MC".  However,
I get the following error:



Error in validObject(.Object) :
  invalid class "dgRMatrix" object: slot j is not increasing inside a
column

The traceback results are:

10: stop(msg, " ", errors, domain = NA)
9: validObject(.Object)
8: initialize(value, ...)
7: initialize(value, ...)
6: new("dgRMatrix", j = z[[1]], p = p0, Dim = as.integer(c(n, n)),
       x = z[[2]])
5: as_dgRMatrix_listw(get("listw", envir = env))
4: .class1(object)
3: as(as_dgRMatrix_listw(get("listw", envir = env)), "CsparseMatrix")
2: LU_setup(env)
1: lagsarlm(fecurrentcombined, data = spssall, listw = lw_test2.csv,
na.action = na.fail, type = "lag", method = "LU", quiet = TRUE,
zero.policy = FALSE, interval = c(-1, 0.999), tol.solve = 1e-20)

The code for creating listw, and the listw summary are as follows:



test2.csv <- read.csv("C:/TIFArticle/KC Exisiting Housing/EHspwt.csv")

class(test2.csv) <- c("spatial.neighbour", class(test2.csv))

of <- ordered(test2.csv$OID)

attr(test2.csv, "region.id") <- levels(of)

test2.csv$OID <- as.integer(of)

test2.csv$NID <- as.integer(ordered(test2.csv$NID))

attr(test2.csv, "n") <- length(unique(test2.csv$OID))



lw_test2.csv <- sn2listw(test2.csv)

lw_test2.csv$style <- "W"

lw_test2.csv





Characteristics of weights list object:

Neighbour list object:

Number of regions: 87223

Number of nonzero links: 348892

Percentage nonzero weights: 0.004585946

Average number of links: 4

Non-symmetric neighbours list



Weights style: W

Weights constants summary:

      n         nn    S0       S1       S2

W 87223 7607851729 87223 27790.89 368025.1




Million thanks in advance for your help.
Shishm

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