Model Selection
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 1, 1 rmse = 139.255086087724
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 1, 1 rmse = 140.890539913043
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 1, 1 rmse = 140.567382295569
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 1, 0.6 rmse = 139.010789933175
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 1, 0.6 rmse = 140.322882651472
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 1, 0.6 rmse = 140.411552602555
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 0.6, 0.6 rmse = 139.001244291099
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 0.6, 0.6 rmse = 140.276667878914
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 0.6, 0.6 rmse = 140.537281858137
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 1, 0.4 rmse = 139.025591411743
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 1, 0.4 rmse = 140.065397061673
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 1, 0.4 rmse = 140.265960819607
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 0.6, 0.4 rmse = 138.96613004196
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 0.6, 0.4 rmse = 139.967858597932
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 0.6, 0.4 rmse = 140.432946327702
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 0.4, 0.4 rmse = 139.131018017459
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 0.4, 0.4 rmse = 139.855973532081
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 0.4, 0.4 rmse = 140.346400785004
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 1, 0 rmse = 139.327658907572
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 1, 0 rmse = 139.827566971016
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 1, 0 rmse = 139.913092253992
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 0.6, 0 rmse = 139.213431029874
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 0.6, 0 rmse = 139.635311856949
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 0.6, 0 rmse = 140.004697616627
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 0.4, 0 rmse = 139.311504323035
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 0.4, 0 rmse = 139.58061907075
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 0.4, 0 rmse = 140.006465599509
## Joining, by = c("year", "Site")
## for distance: in month 1 Month and lag 1, 0, 0 rmse = 139.759725014458
## Joining, by = c("year", "Site")
## for distance: in month 3 Months and lag 1, 0, 0 rmse = 139.677544030951
## Joining, by = c("year", "Site")
## for distance: in month 5 Months and lag 1, 0, 0 rmse = 139.918483152781
## Joining, by = c("year", "Site")
|
sigma
|
loglik
|
aic
|
bic
|
deviance
|
df.residual
|
r2.conditional
|
r2.marginal
|
icc
|
rmse
|
score.log
|
score.spherical
|
|
1
|
-288909.3
|
577830.6
|
577873.9
|
508271.4
|
10106
|
0.9936923
|
0.0562368
|
0.9933164
|
120.9868
|
-Inf
|
0.0044948
|
|
term
|
estimate
|
std.error
|
conf.level
|
conf.low
|
conf.high
|
statistic
|
df.error
|
p.value
|
effect
|
group
|
|
(Intercept)
|
4.8332115
|
0.1773327
|
0.95
|
4.4856457
|
5.1807772
|
27.255046
|
Inf
|
0.000000
|
fixed
|
|
|
Prec
|
0.0002826
|
0.0000113
|
0.95
|
0.0002604
|
0.0003048
|
24.979951
|
Inf
|
0.000000
|
fixed
|
|
|
age
|
0.0076938
|
0.0001061
|
0.95
|
0.0074859
|
0.0079018
|
72.528388
|
Inf
|
0.000000
|
fixed
|
|
|
Prec:age
|
0.0000009
|
0.0000003
|
0.95
|
0.0000002
|
0.0000016
|
2.604716
|
Inf
|
0.009195
|
fixed
|
|
|
SD (Intercept)
|
0.4620753
|
NA
|
0.95
|
NA
|
NA
|
NA
|
NA
|
NA
|
random
|
Individual:Site
|
|
SD (Intercept)
|
0.7881173
|
NA
|
0.95
|
NA
|
NA
|
NA
|
NA
|
NA
|
random
|
Site
|
|
SD (Observations)
|
1.0000000
|
NA
|
0.95
|
NA
|
NA
|
NA
|
NA
|
NA
|
random
|
Residual
|
SPEI
## Loading required package: sp
##
## Attaching package: 'raster'
## The following object is masked from 'package:nlme':
##
## getData
## The following object is masked from 'package:lme4':
##
## getData
## The following object is masked from 'package:dplyr':
##
## select
## Linking to GEOS 3.9.1, GDAL 3.2.1, PROJ 7.2.1; sf_use_s2() is TRUE
## Loading required package: lmomco
## # Package SPEI (1.7) loaded [try SPEINews()].
## [1] "1 of 22 ready"
## [1] "2 of 22 ready"
## [1] "3 of 22 ready"
## [1] "4 of 22 ready"
## [1] "5 of 22 ready"
## [1] "6 of 22 ready"
## [1] "7 of 22 ready"
## [1] "8 of 22 ready"
## [1] "9 of 22 ready"
## [1] "10 of 22 ready"
## Error in spei(NewMonthly2[[i]]$bal, 1) : Error: Data must not contain NAs
## Error in spei(NewMonthly2[[i]]$bal, 3) : Error: Data must not contain NAs
## Error in spei(NewMonthly2[[i]]$bal, 5) : Error: Data must not contain NAs
## [1] "11 of 22 ready"
## [1] "12 of 22 ready"
## [1] "13 of 22 ready"
## [1] "14 of 22 ready"
## [1] "15 of 22 ready"
## [1] "16 of 22 ready"
## [1] "17 of 22 ready"
## [1] "18 of 22 ready"
## [1] "19 of 22 ready"
## [1] "20 of 22 ready"
## [1] "21 of 22 ready"
## [1] "22 of 22 ready"
