Anexo 5: Ajustes polinomiales

Ajuste polinomial de primer grado

train_index <- sample(1:nrow(precip2), 0.7 * nrow(precip2))
test_index <- setdiff(1:nrow(precip2), train_index)
ptos_train <- precip2[train_index, ]
ptos_test  <- precip2[test_index,]
P <- ptos_train

f.1 <- as.formula(rain ~ X + Y) 

P$X <- coordinates(P)[,1]
P$Y <- coordinates(P)[,2]

lm.1 <- lm( f.1, data=P)

dat.1st <- SpatialGridDataFrame(grd, data.frame(var1.pred = predict(lm.1, newdata=grd)))

r   <- raster(dat.1st)
r.m1 <- raster::mask(r, valle2)

tm_shape(r.m1) + 
  tm_raster(n=10, palette="RdBu", midpoint = 43, 
            title="Interpolación con polinomio de 1er orden \n para precipitacion \n(mm)") +
  tm_shape(P) + tm_dots(size=0.02) +
  tm_legend(legend.outside=TRUE)

Ajuste polinomial de segundo grado

f.2 <- as.formula(rain ~ X + Y + I(X*X)+I(Y*Y) + I(X*Y))

P$X <- coordinates(P)[,1]
P$Y <- coordinates(P)[,2]
 
lm.2 <- lm( f.2, data=P)

dat.2nd <- SpatialGridDataFrame(grd, data.frame(var1.pred = predict(lm.2, newdata=grd))) 

r   <- raster(dat.2nd)
r.m <- raster::mask(r, valle2)


tm_shape(r.m) + 
  tm_raster(n=10, palette="RdBu", auto.palette.mapping=FALSE,midpoint = NA,
            title="Interpolación con polinomio de 2do orden \n para precipitacion \n(mm)") +
  tm_shape(P) + tm_dots(size=0.02, col="white") +
  tm_legend(legend.outside=TRUE)

Warning: The argument auto.palette.mapping is deprecated. Please use midpoint for numeric data and stretch.palette for categorical data to control the palette mapping.