Interior Points

Meeting on May 12 2017

To check whether the points is in the interior area

## Loading required package: nlme

## This is mgcv 1.8-15. For overview type 'help("mgcv-package")'.

Project 4D to 3D

## Loading required package: ggplot2

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:taRifx':
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##     distinct

## The following object is masked from 'package:stats':
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## The following object is masked from 'package:graphics':
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3D plot of lat, long, airtemp

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## Warning: Ignoring 2904 observations

3D plot of lat, long, elevation

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3D plot of lat, elevation, airtemp

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## Warning: Ignoring 2904 observations

3D plot of long, elevation, airtemp

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## Warning: Ignoring 2904 observations

In the training set, there is no SAV, but testing set including SAV.

 Test.Site1 <- c("US-Bo1","US-Ne1","US-ARM","US-Ro1", # CRO
                "US-Ced", # CSH
                "US-Ha1","US-WCr","US-MMS", # DBF
                "US-Skr", # EBF
                "US-Ho1","US-Wrc","US-NR1","CA-TP1","US-GLE","US-Me2","US-SP1", # ENF
                "US-Var","US-Wkg","US-FPe", # GRA
                "US-PFa", # MF
                "US-Whs","US-Ses","US-SRC", # OSH
                "US-Los","US-Brw", # WET
                "US-Ton", # WSA
                "US-Wjs"#SAV
                )
 
Train.data1 <- subset(Full.Data,!(site %in% Test.Site1)) 
Test.data1 <- subset(Full.Data,(site %in% Test.Site1))
Obs1 <- Test.data1[,2]

table(Train.data1$species)

## 
##  CRO  CSH  DBF  EBF  ENF  GRA   MF  OSH  SAV  WET  WSA 
## 1932  920 2461  345 6003 2484  920 1219    0  782  529

table(Test.data1$species)

## 
##  CRO  CSH  DBF  EBF  ENF  GRA   MF  OSH  SAV  WET  WSA 
## 1081  230 1334  184 2438  828  483  552  184  598  322

library(mgcv)
Mod.Train6 <- gam(flux ~ s(elevation,bs="tp")
                  + s(airtemp,bs="tp")
                  + ti(elevation,airtemp) # to use this the main effect has to be smoothed?
                  + s(lat,long,bs="ts"),
                  data=Train.data1,
                  na.action = na.exclude)

Pred6 <- predict(Mod.Train6,Test.data1[,-c(1,2)])
PlotPredRes(Obs1,Pred6)