I am trying to use gwr.sel to apply the AIC method for bandwidth selection
in SPGWR. R version is 2.10.1 (used for compatibility with Rpy--however, the
following problem occurs directly from within R). SPGWR version is 0.6-4.
First I run global regression, then gwr()with default CV method for
bandwidth selection with no problems. Then I run "aic" bandwidth selection
method, which outputs bandwidth results. Then I run gwr(), which produces no
output. Perhaps I'm using the wrong command? I can't find many examples of
gwr() implemented with "aic". Please share your ideas if you have any.
Thanks.
> library(spgwr)
Loading required package: sp
Loading required package: maptools
Loading required package: foreign
Loading required package: lattice
NOTE: default kernel and CV criteria changed
see help pages for details
> library(foreign)
> data <-
read.dbf("C:/GIS/Hunter/Thesis/GISData/Parcel/Albany/AlbCnty/Polygon2004/test2.dbf")
> data <- subset(data, GOOGDIST > 0)
> data <- subset(data, ACRES > .5)
> data_lm <- lm(SALE_PRICE ~ ACRES + CUR_TOT_A + HHINC + PERGTBACH, data =
data)
> data_lm_sum <- summary(data_lm)
> tmp<-print(data_lm_sum)
Call:
lm(formula = SALE_PRICE ~ ACRES + CUR_TOT_A + HHINC + PERGTBACH,
data = data)
Residuals:
Min 1Q Median 3Q Max
-890883 -92357 -66457 76176 1550181
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.997e+04 2.566e+04 3.507 0.000483 ***
ACRES -1.999e+03 3.915e+02 -5.106 4.26e-07 ***
CUR_TOT_A 1.993e+00 9.443e-02 21.104 < 2e-16 ***
HHINC -7.636e-02 5.363e-01 -0.142 0.886810
PERGTBACH 9.287e+03 5.020e+04 0.185 0.853272
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: 186700 on 689 degrees of freedom
Multiple R-squared: 0.4061, Adjusted R-squared: 0.4027
F-statistic: 117.8 on 4 and 689 DF, p-value: < 2.2e-16
> data_bw <- gwr.sel(SALE_PRICE ~ ACRES + CUR_TOT_A + HHINC + PERGTBACH ,
data = data, coords = cbind(data$X, data$Y))
Bandwidth: 79378.23 CV score: 2.508302e+13
Bandwidth: 128308.4 CV score: 2.549703e+13
Bandwidth: 49137.69 CV score: 2.444211e+13
Bandwidth: 30448.02 CV score: 2.369592e+13
Bandwidth: 18897.16 CV score: 2.35517e+13
Bandwidth: 17792.42 CV score: 2.365362e+13
Bandwidth: 23918.27 CV score: 2.340727e+13
Bandwidth: 26412.41 CV score: 2.348778e+13
Bandwidth: 23178.31 CV score: 2.339931e+13
Bandwidth: 22740.56 CV score: 2.339894e+13
Bandwidth: 22908.52 CV score: 2.339868e+13
Bandwidth: 22910.54 CV score: 2.339868e+13
Bandwidth: 22909.77 CV score: 2.339868e+13
Bandwidth: 22909.78 CV score: 2.339868e+13
Bandwidth: 22909.78 CV score: 2.339868e+13
Bandwidth: 22909.78 CV score: 2.339868e+13
Bandwidth: 22909.78 CV score: 2.339868e+13
> data_gauss <- gwr(SALE_PRICE ~ ACRES + CUR_TOT_A + HHINC + PERGTBACH, data
= data, coords = cbind(data$X, data$Y), bandwidth = data_bw, hatmatrix =
TRUE)
> data_gauss_sum <- summary(data_gauss)
> print (data_gauss_sum)
Length Class Mode
SDF 1 SpatialPointsDataFrame S4
lhat 481636 -none- numeric
lm 11 -none- list
results 14 -none- list
bandwidth 1 -none- numeric
adapt 0 -none- NULL
hatmatrix 1 -none- logical
gweight 1 -none- character
this.call 6 -none- call
> print (data_gauss)
Call:
gwr(formula = SALE_PRICE ~ ACRES + CUR_TOT_A + HHINC + PERGTBACH,
data = data, coords = cbind(data$X, data$Y), bandwidth = data_bw,
hatmatrix = TRUE)
Kernel function: gwr.Gauss
Fixed bandwidth: 22909.78
Summary of GWR coefficient estimates:
Min. 1st Qu. Median 3rd Qu. Max.
Global
X.Intercept. -2.883e+05 -4.166e+04 1.135e+05 1.655e+05 2.834e+05
89969.4089
ACRES -3.259e+03 -2.678e+03 -1.572e+03 9.080e+02 8.611e+03
-1998.9124
CUR_TOT_A 2.233e-02 1.261e+00 1.628e+00 2.049e+00 2.380e+00
1.9928
HHINC -5.563e+00 -1.219e+00 3.129e-01 2.753e+00 8.023e+00
-0.0764
PERGTBACH -3.023e+05 -9.237e+04 -5.303e+04 -7.264e+03 1.014e+05
9287.3433
Number of data points: 694
Effective number of parameters (residual: 2traceS - traceS'S): 29.87522
Effective degrees of freedom (residual: 2traceS - traceS'S): 664.1248
Sigma (residual: 2traceS - traceS'S): 170145.2
Effective number of parameters (model: traceS): 21.99972
Effective degrees of freedom (model: traceS): 672.0003
Sigma (model: traceS): 169145.3
Sigma (ML): 166442.7
AICc (GWR p. 61, eq 2.33; p. 96, eq. 4.21): 18704.23
AIC (GWR p. 96, eq. 4.22): 18678.59
Residual sum of squares: 1.922601e+13
> data_bw_aic <- gwr.sel(SALE_PRICE ~ ACRES + CUR_TOT_A + HHINC + PERGTBACH
, data = data, coords = cbind(data$X, data$Y), method="aic")
Bandwidth: 79378.23 AIC: 18795.23
Bandwidth: 128308.4 AIC: 18811.03
Bandwidth: 49137.69 AIC: 18768.93
Bandwidth: 30448.02 AIC: 18733.32
Bandwidth: 18897.16 AIC: 18678.52
Bandwidth: 11758.34 AIC: 18593.90
> data_bw_aic_sum <- summary(data_bw_aic)
> data_bw_aic_sum
> print(data_bw_aic)
> data_gauss_aic <- gwr(SALE_PRICE ~ ACRES + CUR_TOT_A + HHINC + PERGTBACH,
data = data, coords = cbind(data$X, data$Y), bandwidth = data_bw_aic,
hatmatrix = TRUE)
>print(data_gauss_aic)
> summary(data_gauss_aic)
>
data looks like this:
UID YEAR X Y LAT LONG ACRES SLOPE
CUR_TOT_A FLOODPER
1 6482 2004 698260.3 1446285 42.80053 -73.73233 0.7309970 1
40000 0.0000000000
5 8554 2004 695351.2 1438002 42.77801 -73.74342 0.8890091 1
7400 0.0000000000
7 15413 2004 696033.0 1431745 42.76088 -73.74108 0.5565335 1
50000 0.0000000000
10 8220 2004 680872.2 1435917 42.77268 -73.79744 0.8693349 1
27200 0.0000000000
11 8221 2004 681023.1 1436053 42.77303 -73.79688 0.8018674 1
25900 0.0000000000
12 8792 2004 691488.3 1439555 42.78245 -73.75765 0.8236566 1
42000 0.0000000000
13 8793 2004 691556.9 1439692 42.78277 -73.75746 0.8610513 1
42000 0.0000000000
14 14411 2004 682812.3 1426310 42.74625 -73.79048 1.9767706 1
150000 0.0000000000
15 14656 2004 688672.5 1432607 42.76348 -73.76833 3.5036509 1
65700 0.0000000000
16 15103 2004 686513.4 1428931 42.75343 -73.77653 4.5957896 1
352800 0.0000000000
19 89916 2004 702825.7 1439163 42.78107 -73.71557 5.4003465 1
23200 0.0000000000
22 93898 2004 704736.3 1432229 42.76197 -73.70865 0.9085830 1
8400 0.0000000000
25 10109 2004 657502.9 1427039 42.74891 -73.88458 3.1770620 1
53600 0.0000000000
26 10296 2004 657568.5 1427583 42.75031 -73.88438 0.9898759 1
39200 0.5419490988
GOOGADDR GOOGDIST
PROP_CLASS SALE_PRICE HHINC
1 1251 New Loudon Rd, Cohoes, NY 12047, USA
21597 311 42500 25964
5 22 Meadow St, Cohoes, NY 12047, USA
19195 311 31500 25964
7 44 Graffin Dr, Latham, NY 12110, USA
18764 311 396500 25964
10 4119-4195 River Rd, Latham, NY 12110, USA
18941 311 71454 16222
11 4119-4195 River Rd, Latham, NY 12110, USA
18941 311 71454 16222
12 112 Dunsbach Ferry Rd, Cohoes, NY 12047, USA
19164 311 65000 16222
13 114 Dunsbach Ferry Rd, Cohoes, NY 12047, USA
19208 311 68000 16222
14 155 Wade Rd, Latham, NY 12110, USA
13289 330 100000 16222
15 100 Sparrowbush Rd, Latham, NY 12110, USA
16458 311 275000 16222
16 4 Stanley Cir, Latham, NY 12110, USA
15605 330 307000 16222
19 28 Edward St, Cohoes, NY 12047, USA
21813 311 114685 51214
22 8 Oxford Cir, Cohoes, NY 12047, USA
22499 311 342551 51214
25 72 Morris Rd, Colonie, NY 12205, USA
14924 330 190000 19865
26 79 Morris Rd, Schenectady, NY 12304, USA
14929 330 18000 19865
PERGTBACH PERLTBACH PERCAPINC
1 0.11521926 0.8847807 14998
5 0.11521926 0.8847807 14998
7 0.11521926 0.8847807 14998
10 0.12627425 0.8737257 12147
11 0.12627425 0.8737257 12147
12 0.12627425 0.8737257 12147
13 0.12627425 0.8737257 12147
14 0.12627425 0.8737257 12147
15 0.12627425 0.8737257 12147
16 0.12627425 0.8737257 12147
19 0.37195452 0.6280455 25915
22 0.37195452 0.6280455 25915
25 0.16253444 0.8374656 10992
26 0.16253444 0.8374656 10992
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