morfoliza

gistfile1.r

```R
---
title: "Analiza - CRO"
author: "Teo"
date: "Sunday, February 15, 2015"
output: html_document
---

```{r}
library(ggplot2)
library(nlme)
library(sp)
library(dplyr)
```

```{r}
cro <- read.table("morfo.txt", header = TRUE, sep = "\t")
str(cro)

cro <- na.omit(cro)
cro$GKY <- cro$GKY + rnorm(nrow(cro))
cro$GKX <- cro$GKX + rnorm(nrow(cro))

levels(cro$locality) <- c("Izvor Spilja Ricina", "Severova spilja", "Luska spilja", 
                          "Pecina spilja", "Ponor Susik", "Rudnica VI", "Sinicic spilja",
                          "Vidovica spilja", "Vranovski ponor", "Zagorska pec")
```

## Model 1
```{r}
lm.G1bl <- lm(S.G1 ~ toto, data = cro)
summary(lm.G1bl)

ggplot(cro, aes(x=toto, y=S.G1)) +
  theme_bw() + 
  geom_point() +
  geom_smooth(method= lm)

confint(lm.G1bl, level = 0.95)
anova(lm.G1bl)
```

## Model 2
```{r}
lm.G2bl <- lm(S.G2~ toto, data = cro)
summary(lm.G2bl)

ggplot(cro, aes(x = toto, y = S.G2)) +
  theme_bw() + 
  geom_point() +
  geom_smooth(method = lm)

confint(lm.G2bl, level = 0.95)
anova(lm.G2bl)
```

## Prostorska avtokorelacija

```{r}
mdl.pac <- gls(resP7 ~ community * flow, data = cro)
mdl.tmp <- gls(resP7 ~ community + flow, data = cro)

AIC(mdl.pac, mdl.tmp)
     
plot(mdl.pac)

mario.vario <- Variogram(mdl.pac, form =~ Xnew + GKY, robust = TRUE, maxDist = 80000, resType = "response")
plot(mario.vario)

# xy <- cro
# coordinates(xy) <- ~ Xnew + GKY
# plot(xy, col = xy@data$community)
coordinates(cro) <- ~ GKX + GKY

gls.spher <- gls(resP7 ~ community * flow, correlation = corSpher(form = ~ GKX + GKY, nugget = TRUE), method = "REML", data = cro)
# gls.lin <- gls(resP7 ~ community * flow, correlation = corLin(form = ~ GKX + GKY, nugget = TRUE), method = "REML",data = cro)
gls.ratio <- gls(resP7 ~ community * flow, correlation = corRatio(form = ~ GKX + GKY, nugget = TRUE), method = "REML", data = cro)
gls.gaus <- gls(resP7 ~ community * flow, correlation = corGaus(form = ~ GKX + GKY, nugget=TRUE), method = "REML",data = cro)
gls.exp <- gls(resP7 ~ community * flow, correlation = corExp(form = ~ GKX + GKY, nugget=TRUE), method = "REML", data = cro)

# AIC(mdl.pac, gls.spher, gls.lin, gls.ratio, gls.gaus, gls.exp)
AIC(mdl.pac, gls.spher, gls.ratio, gls.gaus, gls.exp) # gls.lin ne konvergira (rad)
```
vse isto sranje. Izgleda, da ni avtokorelacije.

## Mešani modeli

```{r}
ggplot(as.data.frame(cro), aes(x = community, y = resP7, color = flow)) +
  theme_bw() +
  geom_point(size = 3) +
  facet_wrap(~ locality)

mdl.lme1 <- lme(resP7 ~ community * flow,random= ~1|locality, method="REML",data = cro)
mdl.noflow <- lme(resP7 ~ community, random = ~ 1|locality, method = "REML", data = cro)
summary(mdl.lme1)

as.data.frame(cro) %>% 
  group_by(flow) %>%
  summarize(mean(resP7))
```

Primerjamo AIC "polnega" modela in modela brez `flow`.
```{r}
AIC(mdl.lme1, mdl.noflow)
```

Model brez `flow` se poslabša. Podpora tezi, da `flow` vpliva na dolžino P7.

## Brez Rudnice

```{r}
nirudnice <- cro[!cro$locality %in% "Rudnica VI", ]
```


```