# NOT RUN { set.seed(123); nn <- 1000 bdata <- data.frame(x2 = runif(nn), x3 = runif(nn)) bdata <- transform(bdata, y1 = rnorm(nn, 1 + 2 * x2), y2 = rnorm(nn, 3 + 4 * x2)) fit1 <- vglm(cbind(y1, y2) ~ x2, binormal(eq.sd = TRUE), data = bdata, trace = TRUE) coef(fit1, matrix = TRUE) constraints(fit1) summary(fit1) # Estimated P(Y1 <= y1, Y2 <= y2) under the fitted model var1 <- loge(2 * predict(fit1)[, "loge(sd1)"], inverse = TRUE) var2 <- loge(2 * predict(fit1)[, "loge(sd2)"], inverse = TRUE) cov12 <- rhobit(predict(fit1)[, "rhobit(rho)"], inverse = TRUE) head(with(bdata, pbinorm(y1, y2, mean1 = predict(fit1)[, "mean1"], mean2 = predict(fit1)[, "mean2"], var1 = var1, var2 = var2, cov12 = cov12))) # }
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