Hi all,
First thanks to everyone who takes the time to respond to messages in this group. It's really a great resource!
I am running a larger pcountOpen model (~1100 sites, 22 primary periods, 12 visits). I am attempting to run a goodness-of-fit test on a cluster computer using AICcmodavg's Nmix.gof.test. When I run the test with a lower number of simulations (1000), it runs but I get a NaN value for chat. I'm moving forward on the assumption (or hope) that that is a problem of not enough simulations and not lack of fit. However, when I attempt to increase the number of simulations to 5k (and I plan to run 10k) I get this error:
"Error in socketAccept(socket = socket, blocking = TRUE, open = "a+b", :
all connections are in use"
My current request from the cluster is 32 cores on a single node with 650GB of memory. So I'm hoping someone with more experience with cluster computers and parboot might:
- Have a suggestion for best practices for running Nmix.gof.test() on a cluster. So that might look like is it better to run this (or any) GOF test with more nodes, cores, memory etc. Any insight would be appreciated.
- Know what is going on with that socket error?
The summary output of my unmarkedFramePCO object is below. The NAs are mostly structural placeholders for when there were fewer than 12 visits per year. Though some of the yearly site covariates do not yet have data for the final year. I'm currently trying to run the goodness-of-fit test on the model below rather than a global or set of sub-global models.
system.time(go.spei90d_july_p_HOR <-
pcountOpen(
lambda = ~HOR,
gamma = ~gm_spei90d_p,
omega = ~HOR,
p = ~Season,
umf_bre,
K=68,
#se= FALSE,
#starts = inits,
dynamics = "gompertz"
))
unmarkedFrame Object
1181 sites
Maximum number of observations per site: 264
Mean number of observations per site: 4.84
Number of primary survey periods: 22
Number of secondary survey periods: 12
Sites with at least one detection: 1165
Tabulation of y observations:
0 1 2 3 4 5 6 7 8 9 10 11 12
659 3036 868 393 248 122 87 61 46 41 17 20 23
13 14 15 16 17 18 19 20 21 22 23 24 25
12 11 7 3 5 7 3 3 8 4 6 2 2
26 27 28 29 30 32 36 39 40 45 46 48 <NA>
2 2 1 2 1 2 1 2 1 1 1 1 306073
Site-level covariates:
bd_result HOR nndist DuPont private
Min. :0.0000 Min. :0.0000 Min. : 0.637 Min. :0.0000 Min. :0.0000
1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.: 20.028 1st Qu.:0.0000 1st Qu.:0.0000
Median :0.0000 Median :0.0000 Median : 45.360 Median :1.0000 Median :0.0000
Mean :0.1611 Mean :0.1016 Mean : 134.210 Mean :0.5868 Mean :0.2049
3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.: 113.463 3rd Qu.:1.0000 3rd Qu.:0.0000
Max. :2.0000 Max. :1.0000 Max. :5657.168 Max. :1.0000 Max. :1.0000
NA's :1032
Observation-level covariates:
J_date Season
Min. : 17.0 Spring: 1437
1st Qu.:150.0 Summer: 1683
Median :252.0 Fall : 2242
Mean :221.7 Winter: 349
3rd Qu.:293.0 NA's :306073
Max. :365.0
NA's :306073
Yearly-site-level covariates:
pdsi_aug_c.V1 pdsi_july_c.V1 pdsi_july_p.V1 pdsi_aug_p.V1 tmax_july_c.V1
Min. :-1.5937 Min. :-1.8284 Min. :-1.7713 Min. :-1.5210 Min. :-3.5197
1st Qu.:-0.6979 1st Qu.:-0.8107 1st Qu.:-0.7508 1st Qu.:-0.7416 1st Qu.:-0.6595
Median :-0.3033 Median :-0.2126 Median :-0.3480 Median :-0.3297 Median :-0.0424
Mean : 0.0000 Mean : 0.0000 Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
3rd Qu.: 0.7735 3rd Qu.: 0.7218 3rd Qu.: 0.7560 3rd Qu.: 0.7105 3rd Qu.: 0.6465
Max. : 2.3190 Max. : 2.2126 Max. : 2.2808 Max. : 2.3878 Max. : 4.3779
NA's :1181 NA's :1181 NA's :1181 NA's :1181 NA's :1181
tmax_july_p.V1 tmax_aug_c.V1 tmax_aug_p.V1 tmin_dec_c.V1 tmin_jan_c.V1
Min. :-3.5319 Min. :-3.0506 Min. :-3.0741 Min. :-2.9035 Min. :-2.8460
1st Qu.:-0.6651 1st Qu.:-0.7425 1st Qu.:-0.7123 1st Qu.:-0.7157 1st Qu.:-0.7050
Median :-0.0246 Median : 0.0027 Median :-0.0181 Median : 0.2886 Median :-0.1785
Mean : 0.0000 Mean : 0.0000 Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
3rd Qu.: 0.6432 3rd Qu.: 0.5299 3rd Qu.: 0.5656 3rd Qu.: 0.5742 3rd Qu.: 0.7016
Max. : 4.3646 Max. : 4.3156 Max. : 4.1261 Max. : 2.7258 Max. : 2.3145
NA's :1181 NA's :1181 NA's :1181 NA's :1181 NA's :1181
tmin_dec_p.V1 tmin_jan_p.V1 gm_spei180d gm_spei1y gm_spei2y
Min. :-2.9317 Min. :-2.8940 Min. :-2.0900 Min. :-2.0900 Min. :-2.09000
1st Qu.:-0.7325 1st Qu.:-0.6990 1st Qu.:-0.7100 1st Qu.:-0.6200 1st Qu.:-0.80000
Median : 0.2771 Median :-0.1593 Median :-0.3200 Median :-0.1000 Median:0.03000
Mean : 0.0000 Mean : 0.0000 Mean :-0.0443 Mean : 0.1445 Mean : 0.09956
3rd Qu.: 0.5642 3rd Qu.: 0.7392 3rd Qu.: 0.5400 3rd Qu.: 1.1300 3rd Qu.: 0.80000
Max. : 2.7270 Max. : 2.3966 Max. : 2.0900 Max. : 2.0900 Max. : 2.09000
NA's :1181 NA's :1181
gm_spei30d_p gm_spei90d_p
Min. :-2.09000 Min. :-2.09000
1st Qu.:-0.54000 1st Qu.:-0.62000
Median :-0.17000 Median :-0.03000
Mean :-0.01057 Mean : 0.07694
3rd Qu.: 0.63000 3rd Qu.: 1.13000
Max. : 2.09000 Max. : 2.09000