Report of SpAnova

In spANOVA: Spatial Analysis of Field Trials Experiments using Geostatistics and Spatial Autoregressive Model

Semivariogram

Correlation function: r params$CorF.

plot(params$modelVariog)
lines(params$modelVariofit, col = 1)

Semivariogram Parameter Estimates

knitr::kable(params$semiPar)

Analysis of Variance

knitr::kable(params$tab)

Checking the Residuals

res <- params$modelGeo$residuals
par(mfrow = c(1,2))
hist(res, xlab = "Residuals", main = "", freq = FALSE)
lines(density(res))
qqnorm(res)
qqline(res)

res <- params$modelGeo$residuals
plot(res, ylab = "Residuals")

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knitr::kable(params$table)

  if (params$table$P.value[1] < 0.05) {
    textRes <- "According to Shapiro-Wilk normality test at 5% of significance, residuals cannot be considered normal."
  }else {
    textRes <- "According to Shapiro-Wilk normality test at 5% of significance, residuals can be considered normal."
  }

  if (params$table$P.value[2] < 0.05) {
    textRes2 <- "According to Moran I test at 5% of significance, there is spatial correlation among the residuals."
  }else {
    textRes2 <- "According to Moran I test at 5% of significance, there is no spatial correlation among the residuals."
  }

r textRes

r textRes2

Multiple Comparison Procedure

Procedure: r params$McompName

knitr::kable(params$McomP)

Treatments with the same letter are not significantly different at 5% of significance.

spANOVA documentation built on June 11, 2021, 9:07 a.m.