Tables

Primary programmer: John Fieberg | Secondary programmer: Althea A. ArchMiller

Date: 20160805

Tables in: Fieberg et al. Species distribution models: Predictive snipers or shots in the dark?

Preamble

Load libraries

remove(list=ls())
library(xtable)

Table 1. Missing predictor example

# Scenario 1 
load("examples/Regmods/Regmods_corr00.R")
train.correct.corr00 <- train.correct
train.missingprecip.corr00 <- train.missingprecip

# Scenario 2
load("examples/Regmods/Regmods_corrNN.R")
train.correct.corrNN <- train.correct
train.missingprecip.corrNN <- train.missingprecip

# Scenario 3
load("examples/Regmods/Regmods_corrPN.R")
train.correct.corrPN <- train.correct
train.missingprecip.corrPN <- train.missingprecip

Create coefficient Table

coeftab<-matrix(NA, 3, 8)
coeftab[1:3,1]<-c(0, -0.3, 0.3)
coeftab[1,2:3]<-summary(train.missingprecip.corr00)$coefficients[2,1:2]
coeftab[2,2:3]<-summary(train.missingprecip.corrNN)$coefficients[2,1:2]
coeftab[3,2:3]<-summary(train.missingprecip.corrPN)$coefficients[2,1:2]
coeftab[1,5:6]<-summary(train.correct.corr00)$coefficients[2,1:2]
coeftab[1,7:8]<-summary(train.correct.corr00)$coefficients[3,1:2]
coeftab[2,5:6]<-summary(train.correct.corrNN)$coefficients[2,1:2]
coeftab[2,7:8]<-summary(train.correct.corrNN)$coefficients[3,1:2]
coeftab[3,5:6]<-summary(train.correct.corrPN)$coefficients[2,1:2]
coeftab[3,7:8]<-summary(train.correct.corrPN)$coefficients[3,1:2]

coeftab<-round(coeftab,3)
xtable::xtable(coeftab)
## % latex table generated in R 3.3.0 by xtable 1.8-2 package
## % Wed Oct 26 13:02:59 2016
## \begin{table}[ht]
## \centering
## \begin{tabular}{rrrrrrrrr}
##   \hline
##  & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 \\ 
##   \hline
## 1 & 0.00 & 0.42 & 0.05 &  & 0.42 & 0.06 & -1.04 & 0.07 \\ 
##   2 & -0.30 & 0.80 & 0.06 &  & 0.53 & 0.06 & -0.99 & 0.07 \\ 
##   3 & 0.30 & 0.27 & 0.05 &  & 0.57 & 0.06 & -0.97 & 0.06 \\ 
##    \hline
## \end{tabular}
## \end{table}

Table 2. Non-linear example

load("examples/Regmods/Regmods_T.R")

Create coefficient Table

coeftab<-matrix(NA, 2, 4)
coeftab[1,1:2]<-summary(train.misspec)$coefficients[2,1:2]
coeftab[2,1:2]<-summary(train.correct)$coefficients[2,1:2]
coeftab[2,3:4]<-summary(train.correct)$coefficients[3,1:2]

coeftab<-round(coeftab,3)
xtable::xtable(coeftab)
## % latex table generated in R 3.3.0 by xtable 1.8-2 package
## % Wed Oct 26 13:02:59 2016
## \begin{table}[ht]
## \centering
## \begin{tabular}{rrrrr}
##   \hline
##  & 1 & 2 & 3 & 4 \\ 
##   \hline
## 1 & 0.24 & 0.05 &  &  \\ 
##   2 & 2.21 & 0.35 & -1.05 & 0.17 \\ 
##    \hline
## \end{tabular}
## \end{table}

Table 3. MN moose example

load("examples/Regmods/SSF1_full.R")
load("examples/Regmods/SSF2_reduc.R")
load("examples/Regmods/SSF3_reduc.R")

Create coefficient Table

stargazer::stargazer(ssf.train.full, ssf.train.reduc1, ssf.train.reduc2, 
                     star.cutoffs=NA, table.layout="#tn" )
## Error in .summary.object$coef: $ operator is invalid for atomic vectors

Footer

Session Information

sessionInfo()
## R version 3.3.0 (2016-05-03)
## Platform: x86_64-apple-darwin13.4.0 (64-bit)
## Running under: OS X 10.11.6 (El Capitan)
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] xtable_1.8-2       uhcplots_0.1.0     devtools_1.12.0   
## [4] dismo_1.1-1        raster_2.5-8       sp_1.2-3          
## [7] knitr_1.14         KernSmooth_2.23-15 ezknitr_0.6       
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_0.12.7       magrittr_1.5      MASS_7.3-45      
##  [4] lattice_0.20-34   R6_2.2.0          stringr_1.1.0    
##  [7] httr_1.2.1        tools_3.3.0       grid_3.3.0       
## [10] R.oo_1.20.0       stargazer_5.2     git2r_0.15.0     
## [13] withr_1.0.2       digest_0.6.10     formatR_1.4      
## [16] R.utils_2.4.0     curl_2.2          memoise_1.0.0    
## [19] evaluate_0.10     mime_0.5          stringi_1.1.2    
## [22] R.methodsS3_1.7.1 markdown_0.7.7

Spun with: ezspin(file = “examples/tables.R”, out_dir =“examples/output”, fig_dir = “figures”, keep_md = FALSE)