library("bspmma") data("breast.17") breast.data <- as.matrix(breast.17) set.seed(1) breast.c1 <- dirichlet.c(breast.data, ncycles=4000, M=5) set.seed(1) breast.c2 <- dirichlet.c(breast.data, ncycles=4000, M=1000) # Next three lines require package coda ## library("coda") breast.coda <- mcmc(breast.c1$chain) autocorr.plot(breast.coda[,c(15:19)]) ## breast.c1c2 <- list("5"=breast.c1$chain, "1000"= breast.c2$chain) draw.post(breast.c1c2, burnin=100) describe.post(breast.c1c2, burnin=100) data("ddtm.s") ddtm.s ddtm.s$treat.deaths <- ddtm.s$treat.deaths + .5 ddtm.s$treat.total <- ddtm.s$treat.total + 1 ddtm.s$cont.deaths <- ddtm.s$cont.deaths + .5 ddtm.s$cont.total <- ddtm.s$cont.total + 1 attach(ddtm.s) or <- (treat.deaths / (treat.total - treat.deaths)) / (cont.deaths / (cont.total - cont.deaths)) lor <- log(or) se.lor <- ( (treat.total / (treat.deaths * (treat.total - treat.deaths))) + (cont.total / (cont.deaths * (cont.total - cont.deaths))) )^.5 ddtm.14 <- data.frame(psi.hat=lor, se.psi.hat=se.lor) ddtm.s.data <- as.matrix(ddtm.14) set.seed(1) ddtm.s.c1 <- dirichlet.c(ddtm.s.data, ncycles=4000, M=5) set.seed(1) ddtm.s.c2 <- dirichlet.c(ddtm.s.data, ncycles=4000, M=20) set.seed(1) ddtm.s.c3 <- dirichlet.c(ddtm.s.data, ncycles=4000, M=100) ddtm.s.l1 <- list("5"=ddtm.s.c1$chain, "20"=ddtm.s.c2$chain, "100"=ddtm.s.c3$chain) draw.post(ddtm.s.l1, burnin=100) describe.post(ddtm.s.l1, burnin=100) chain1.list <- bf1(breast.data, ncycles=5000, burnin=1000) cc <- bf2(chain1.list) chain2.list <- bf1(breast.data, seed=2, ncycles=5000, burnin=1000) breast.bfco <- bf.c.o(from=.8, incr=.2, to=20, cc=cc, mat.list=chain2.list) draw.bf(breast.bfco) breast.bfo <- bf.o(from=.8, incr=.2, to=20, cc=cc, mat.list=chain2.list) draw.bf(breast.bfo) breast.bfo$y[9]/breast.bfo$yinfinity