library(aster) library(numDeriv) do.chisq.test <- function(x, k, mu, max.bin) { stopifnot(all(x > k)) stopifnot(k + 1 < max.bin) xx <- seq(k + 1, max.bin) yy <- dpois(xx, mu) yy[length(yy)] <- ppois(max.bin - 1, mu, lower.tail = FALSE) pp <- yy / sum(yy) ecc <- length(x) * pp if (any(ecc < 5.0)) warning("violates rule of thumb about > 5 expected in each cell") cc <- tabulate(x, max.bin) cc <- cc[xx] cc[length(cc)] <- nsim - sum(cc[- length(cc)]) chisqstat <- sum((cc - ecc)^2 / ecc) pval <- pchisq(chisqstat, length(ecc) - 1, lower.tail = FALSE) if (exists("save.min.pval")) { save.min.pval <<- min(pval, save.min.pval) save.ntests <<- save.ntests + 1 } else { save.min.pval <<- pval save.ntests <<- 1 } list(chisqstat = chisqstat, df = length(ecc) - 1, pval = pval, observed = cc, expected = ecc, x = xx) } set.seed(42) nsim <- 1e4 mu <- 10 k <- 2 x <- rktp(nsim, k, mu) chisqout1 <- do.chisq.test(x, k, mu, 22) mu <- 3.5 k <- 2 x <- rktp(nsim, k, mu) chisqout2 <- do.chisq.test(x, k, mu, 11) mu <- 2.5 k <- 2 x <- rktp(nsim, k, mu) chisqout3 <- do.chisq.test(x, k, mu, 10) mu <- 1.5 k <- 2 x <- rktp(nsim, k, mu) chisqout4 <- do.chisq.test(x, k, mu, 8) mu <- 0.5 k <- 2 x <- rktp(nsim, k, mu) chisqout5 <- do.chisq.test(x, k, mu, 6) nsim <- 1e5 mu <- 0.1 k <- 2 x <- rktp(nsim, k, mu) chisqout6 <- do.chisq.test(x, k, mu, 5) mu <- 0.01 k <- 2 x <- rktp(nsim, k, mu) chisqout7 <- do.chisq.test(x, k, mu, 4) mu <- 1.5 xpred <- 0:10 save.seed <- .Random.seed x <- rktp(xpred, k, mu, xpred) .Random.seed <- save.seed my.x <- rep(0, length(xpred)) for (i in seq(along = xpred)) if (xpred[i] > 0) for (j in 1:xpred[i]) my.x[i] <- my.x[i] + rktp(1, k, mu) all.equal(x, my.x) k <- 5 mu <- pi x <- rktp(nsim, k, mu) chisqout8 <- do.chisq.test(x, k, mu, 14) k <- 10 mu <- exp(2) x <- rktp(nsim, k, mu) chisqout9 <- do.chisq.test(x, k, mu, 22) cat("number of tests:", save.ntests, "\n") save.ntests * save.min.pval > 0.05 ##### set.seed(42) nind <- 25 nnode <- 1 ncoef <- 1 k <- 2 pred <- 0 fam <- 4 theta <- 4 / 3 mu <- exp(theta) x <- rpois(100, mu) x <- x[x > k] x <- x[1:nind] modmat <- matrix(1, nrow = nind, ncol = 1) out <- mlogl(theta, pred, fam, x, modmat, modmat, deriv = 2, type = "conditional") xxx <- seq(0, 100) ppp <- dpois(xxx, mu) ppp[xxx <= k] <- 0 ppp <- ppp / sum(ppp) tau <- sum(xxx * ppp) all.equal(sum(x - tau), - out$gradient) all.equal(length(x) * sum((xxx - tau)^2 * ppp), as.vector(out$hessian)) foo <- function(theta) { stopifnot(is.numeric(theta)) stopifnot(is.finite(theta)) stopifnot(length(theta) == 1) mlogl(theta, pred, fam, x, modmat, modmat, type = "conditional")$value } g <- grad(foo, theta) all.equal(g, out$gradient) h <- hessian(foo, theta) all.equal(h, out$hessian) foo <- new.env(parent = emptyenv()) bar <- suppressWarnings(try(load("ktp.rda", foo), silent = TRUE)) if (inherits(bar, "try-error")) { save(list = c(paste("chisqout", 1:9, sep = ""), "out"), file = "ktp.rda") } else { print(all.equal(chisqout1, foo$chisqout1)) print(all.equal(chisqout2, foo$chisqout2)) print(all.equal(chisqout3, foo$chisqout3)) print(all.equal(chisqout4, foo$chisqout4)) print(all.equal(chisqout5, foo$chisqout5)) print(all.equal(chisqout6, foo$chisqout6)) print(all.equal(chisqout7, foo$chisqout7)) print(all.equal(chisqout8, foo$chisqout8)) print(all.equal(chisqout9, foo$chisqout9)) print(all.equal(out, foo$out)) }