@@ -77,21 +77,6 @@ InventoryGrowthFusionDiagnostics <- function(jags.out, combined=NULL) {
7777 vars <- c(vars ,which(colnames(out )== " deviance" ))
7878 }
7979
80-
81- # # rebuild coda for just vars
82- var.out <- coda :: as.mcmc.list(lapply(jags.out ,function (x ){ x [,vars ]}))
83-
84- # # convergence
85- coda :: gelman.diag(var.out )
86-
87- # ### Diagnostic plots
88- plot(var.out )
89-
90- if (" deviance" %in% colnames(out )){
91- graphics :: hist(out [," deviance" ])
92- vars <- c(vars ,which(colnames(out )== " deviance" ))
93- }
94-
9580 # # rebuild coda for just vars
9681 var.out <- coda :: as.mcmc.list(lapply(jags.out ,function (x ){ x [,vars ]}))
9782
@@ -124,19 +109,6 @@ InventoryGrowthFusionDiagnostics <- function(jags.out, combined=NULL) {
124109 graphics :: abline(h = 0 , lty = 2 )
125110 }
126111
127- graphics :: par(mfrow = c(1 , 1 ))
128- # ## alpha
129- alpha.cols <- grep(" alpha" , colnames(out ))
130- if (length(alpha.cols ) > 0 ) {
131- alpha.ord <- 1 : length(alpha.cols )
132- ci.alpha <- apply(out [, alpha.cols ], 2 , stats :: quantile , c(0.025 , 0.5 , 0.975 ))
133- plot(alpha.ord , ci.alpha [2 , ], type = " n" ,
134- ylim = range(ci.alpha , na.rm = TRUE ), ylab = " Random Effects" )
135- PEcAn.visualization :: ciEnvelope(alpha.ord , ci.alpha [1 , ], ci.alpha [3 , ], col = " lightBlue" )
136- graphics :: lines(alpha.ord , ci.alpha [2 , ], lty = 1 , lwd = 2 )
137- graphics :: abline(h = 0 , lty = 2 )
138- }
139-
140112 # ## YEAR
141113 year.cols <- grep(" year" , colnames(out ))
142114 if (length(year.cols > 0 )) {
0 commit comments