require(glarma) ### Boat Race: data(OxBoatRace) y1 <- OxBoatRace$Camwin n1 <- rep(1, length(OxBoatRace$Year)) Y <- cbind(y1, n1 - y1) X <- cbind(OxBoatRace$Intercept, OxBoatRace$Diff) colnames(X) <- c("Intercept", "Weight Diff") oxcamglm <- glm(Y ~ Diff + I(Diff^2), data = OxBoatRace, family = binomial(link = "logit"), x = TRUE) X <- oxcamglm$x glarmamod <- glarma(Y, X, thetaLags = c(1, 2), type = "Bin", method = "NR", residuals = "Pearson", maxit = 100, grad = 1e-6) summary(glarmamod) par(mfrow=c(3,2)) plot(glarmamod) ### model adequate - test using randomized PIT? rt <- normRandPIT(glarmamod)$rt par(mfrow = c(2,2)) hist(rt, main = "Histogram of Randomized Residuals", xlab = expression(r[t])) qqnorm(rt, main = "Q-Q Plot of Randomized Residuals" ) abline(0, 1, lty = 2) acf(rt, main = "ACF of Randomized Residuals") pacf(rt, main = "PACF of Randomized Residuals")
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