[r-cran-coda] 36/60: Imported Upstream version 0.14-4
Andreas Tille
tille at debian.org
Fri Dec 16 12:11:25 UTC 2016
This is an automated email from the git hooks/post-receive script.
tille pushed a commit to branch master
in repository r-cran-coda.
commit 7d7d0cc8dc094ffd3ef5646da356f6d6aebb6c0a
Author: Andreas Tille <tille at debian.org>
Date: Fri Dec 16 12:10:00 2016 +0100
Imported Upstream version 0.14-4
---
CHANGELOG | 4 +
DESCRIPTION | 10 +--
R/gelman.R | 19 +++--
data/line.R | 230 -----------------------------------------------------
data/line.rda | Bin 0 -> 9599 bytes
inst/CITATION | 17 ++++
man/gelman.diag.Rd | 16 +++-
man/gelman.plot.Rd | 7 +-
8 files changed, 53 insertions(+), 250 deletions(-)
diff --git a/CHANGELOG b/CHANGELOG
index 5581466..90ff908 100644
--- a/CHANGELOG
+++ b/CHANGELOG
@@ -1,3 +1,7 @@
+0.14-3
+- Fixed documentation errors in gelman.diag (Thanks to Peng Yu)
+- Added CITATION file
+
0.14-2
- Fix documentation bugs (Thanks to Kurt Hornik)
diff --git a/DESCRIPTION b/DESCRIPTION
index aea75b9..d1fa158 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,13 +1,13 @@
Package: coda
-Version: 0.14-2
-Date: 2010-12-08
+Version: 0.14-4
+Date: 2011-05-20
Title: Output analysis and diagnostics for MCMC
Author: Martyn Plummer, Nicky Best, Kate Cowles, Karen Vines
-Maintainer: Martyn Plummer <plummer at iarc.fr>
+Maintainer: Martyn Plummer <plummerM at iarc.fr>
Depends: R (>= 2.5.0), lattice
Description: Output analysis and diagnostics for Markov Chain Monte
Carlo simulations.
License: GPL (>= 2)
-Packaged: 2010-12-08 13:41:18 UTC; martyn
+Packaged: 2011-05-20 11:16:02 UTC; martyn
Repository: CRAN
-Date/Publication: 2010-12-09 11:29:20
+Date/Publication: 2011-05-20 12:41:27
diff --git a/R/gelman.R b/R/gelman.R
index 561e4e2..203938b 100644
--- a/R/gelman.R
+++ b/R/gelman.R
@@ -92,11 +92,7 @@
R2.estimate <- R2.fixed + R2.random
R2.upper <- R2.fixed + qf((1 + confidence)/2, B.df, W.df) * R2.random
psrf <- cbind(sqrt(df.adj * R2.estimate), sqrt(df.adj * R2.upper))
- dimnames(psrf) <- list(xnames,
- c("Point est.",
- paste(50 * (1+confidence), "% quantile", sep = ""))
- )
-
+ dimnames(psrf) <- list(xnames, c("Point est.", "Upper C.I."))
out <- list(psrf = psrf, mpsrf=mpsrf)
class(out) <- "gelman.diag"
@@ -162,7 +158,7 @@
"gelman.plot" <-
function (x, bin.width = 10, max.bins = 50, confidence = 0.95,
- transform = FALSE, auto.layout = TRUE, ask,
+ transform = FALSE, autoburnin = TRUE, auto.layout = TRUE, ask,
col = 1:2, lty = 1:2, xlab = "last iteration in chain",
ylab = "shrink factor", type = "l", ...)
{
@@ -180,7 +176,8 @@
if (auto.layout)
oldpar <- par(mfrow = set.mfrow(Nchains = nchain(x), Nparms = nvar(x)))
y <- gelman.preplot(x, bin.width = bin.width, max.bins = max.bins,
- confidence = confidence)
+ confidence = confidence, transform = transform,
+ autoburnin = autoburnin)
all.na <- apply(is.na(y$shrink[, , 1, drop = FALSE]), 2, all)
if (!any(all.na))
for (j in 1:nvar(x)) {
@@ -201,8 +198,9 @@
}
"gelman.preplot" <-
- function (x, confidence = 0.95, transform = FALSE, bin.width = 10,
- max.bins = 50)
+ function (x, bin.width = bin.width, max.bins = max.bins,
+ confidence = confidence, transform = transform,
+ autoburnin = autoburnin)
{
x <- as.mcmc.list(x)
if (niter(x) <= 50)
@@ -219,7 +217,8 @@
for (i in 1:(nbin + 1)) {
shrink[i, , ] <- gelman.diag(window(x, end = last.iter[i]),
confidence = confidence,
- transform = transform)$psrf
+ transform = transform,
+ autoburnin = autoburnin)$psrf
}
all.na <- apply(is.na(shrink[, , 1, drop = FALSE]), 2, all)
if (any(all.na)) {
diff --git a/data/line.R b/data/line.R
deleted file mode 100644
index d9c397a..0000000
--- a/data/line.R
+++ /dev/null
@@ -1,230 +0,0 @@
-"line" <-
-structure(list(line1 = structure(c(7.17313, 2.95253, 3.66989,
-3.31522, 3.70544, 3.5791, 2.70206, 2.96136, 3.53406, 2.09471,
-3.06524, 2.73901, 3.08929, 2.70413, 2.52174, 3.73216, 2.67339,
-3.01779, 2.70123, 2.97837, 2.87646, 3.19134, 2.79708, 3.25934,
-2.73704, 2.71863, 3.01749, 2.984, 2.73648, 2.55982, 2.94331,
-3.27086, 3.55436, 2.80668, 3.18001, 3.07977, 2.77286, 2.74566,
-3.67006, 2.24932, 3.08757, 2.56762, 2.80828, 3.76523, 3.10116,
-3.01902, 2.65918, 3.52618, 2.43358, 2.57103, 3.55572, 3.08102,
-3.06265, 2.57951, 2.69831, 2.6604, 3.1768, 2.92196, 1.73505,
-3.46348, 2.99482, 3.18707, 3.2433, 3.3528, 3.12026, 3.27727,
-3.30783, 2.68048, 3.31009, 2.8779, 3.21578, 3.27217, 3.21431,
-3.4163, 2.72993, 3.83811, 2.7769, 3.10277, 0.858013, 1.72668,
-2.2129, 3.13023, 3.11833, 2.52852, 3.19425, 2.33602, 3.86727,
-2.45181, 2.53356, 2.33611, 2.71644, 3.36774, 2.49752, 2.98218,
-2.49989, 2.92943, 2.86987, 4.08664, 2.92904, 2.87937, 3.5247,
-2.6994, 3.2374, 2.79161, 3.0065, 2.84989, 2.92812, 3.09409, 2.98947,
-3.05823, 3.16941, 3.00681, 2.87709, 2.76276, 3.18145, 2.36106,
-2.81812, 3.08823, 2.65743, 2.8572, 3.33833, 2.80197, 2.95402,
-2.95727, 3.19123, 3.43451, 2.59671, 3.60602, 2.68363, 3.56141,
-3.16793, 3.2417, 3.3542, 2.98939, 2.34584, 3.03147, 3.16633,
-2.56506, 3.01896, 3.17286, 2.80791, 2.92504, 3.02911, 2.85911,
-3.28071, 3.43015, 2.3898, 1.67055, 3.81164, 2.43832, 2.92065,
-1.37547, 3.23811, 2.96203, 2.83998, 2.36596, 3.51832, 2.59301,
-3.08633, 2.87675, 3.16977, 2.81822, 2.48206, 3.28322, 2.51132,
-3.01153, 3.25603, 2.98599, 2.93238, 2.12555, 3.5398, 2.96786,
-2.73922, 2.76325, 2.89286, 3.41665, 2.84412, 2.69208, 3.87634,
-2.70917, 3.23347, 3.25577, 2.70044, 2.83369, 3.2501, 3.12599,
-3.16206, 2.90532, 3.35174, 3.36722, 2.73076, 3.26922, 2.81658,
-2.95479, 2.71722, 3.02135, 3.13198, 4.07261, 2.84968, 2.69468,
--1.5662, 1.50337, 0.628157, 1.18272, 0.490437, 0.20697, 0.882553,
-1.08515, 1.06926, 1.48077, 0.378349, 0.444712, -0.01306, 1.15585,
-0.856368, 0.657461, 0.594411, 0.88777, 0.745918, 0.993619, 1.02806,
-0.553611, 1.01886, 0.470345, 0.520167, 0.89238, 0.68696, 0.798954,
-0.688647, 0.579934, 0.844434, 0.810385, 0.872753, 0.895408, 0.827359,
-0.919973, 0.926044, 0.522444, 1.05851, 1.32707, 0.674701, 0.746217,
-1.14114, 1.24147, 0.791581, 0.938256, 0.522189, 0.718395, 0.928954,
-0.57796, 1.07794, 0.812967, 1.04835, 0.993271, 0.781727, 0.306433,
-0.58444, 0.55981, 0.88081, 1.01651, 0.876193, 0.650802, 0.75265,
-0.948834, 0.557148, 0.99243, 0.6986, 0.78952, 0.570903, 0.725568,
-1.16533, 0.453463, 0.871724, 0.889113, 0.507765, 0.414795, 0.87789,
-0.633498, 0.736897, -0.568545, 0.770004, 0.869198, 0.665951,
-0.758507, 0.742198, 1.02311, 0.969699, 0.580553, 1.14088, 0.582853,
-0.677865, 0.652573, 0.952581, 1.1587, 0.999131, 1.09971, 1.02759,
-0.571576, 0.756901, 0.927734, 0.753859, 0.494313, 0.510782, 0.793101,
-1.10834, 0.658604, 0.788326, 0.866193, 0.884201, 0.507964, 0.179421,
-0.718163, 0.874446, 1.01166, 0.626119, 0.808673, 0.52271, 1.06545,
-0.902426, 0.380372, 0.659257, 0.68071, 0.794731, 0.680552, 0.508912,
-0.494933, 1.17763, 1.22197, 0.545816, 0.965099, 0.677669, 0.688658,
-1.06926, 0.344008, 1.09068, 1.02111, 0.691322, 0.364369, 0.915177,
-0.566777, 1.15452, 0.625684, 0.708469, 0.984351, 0.576846, 0.228625,
-1.40307, 1.21012, 0.143615, 1.4046, 1.32799, 0.0254974, 1.17005,
-1.28567, 1.51562, 0.842245, 0.852613, 0.780749, 0.967637, 0.810536,
-0.858167, 0.960625, 0.613509, 1.38389, 1.22199, 0.93934, 0.479022,
-0.684411, 0.907639, 0.694256, 0.762828, 1.08536, 0.737203, 0.79847,
-0.605098, 1.01106, 1.29919, -0.116987, 0.645465, 0.868414, 0.934646,
-0.841893, 0.864243, 1.03498, 0.784894, 1.28125, 0.594917, 1.23255,
-0.788097, 0.929231, 0.823524, 0.748782, 0.625626, 0.742992, 0.733012,
-0.598408, 0.654669, 1.19037, 0.472082, 0.669647, 11.2331, 4.88649,
-1.39734, 0.662879, 1.36213, 1.0435, 1.29043, 0.459322, 0.634257,
-0.912919, 1.1885, 0.576963, 2.40033, 1.79423, 0.943078, 0.903465,
-0.731041, 0.622143, 0.790993, 0.740969, 0.58258, 0.710707, 0.870071,
-1.00433, 1.03022, 1.08587, 0.572809, 0.716056, 0.636699, 0.563391,
-0.848744, 0.516244, 0.642656, 0.554613, 0.695308, 0.617855, 0.425071,
-0.603549, 0.764704, 0.907059, 0.840521, 0.812011, 0.612573, 1.70232,
-0.644559, 0.481628, 0.641244, 0.805918, 0.957325, 0.676466, 0.743322,
-0.951599, 0.595749, 0.462307, 0.746122, 0.958645, 0.764432, 0.527422,
-1.74938, 1.09919, 0.493587, 0.473889, 0.442078, 0.590437, 0.913574,
-0.667202, 0.772119, 0.511031, 0.47078, 0.551933, 0.785661, 0.902284,
-0.420702, 0.872218, 1.51717, 1.27235, 0.70261, 0.504571, 2.0531,
-2.2977, 1.38751, 0.818279, 0.326157, 0.79268, 0.783918, 0.714941,
-0.756979, 0.972415, 0.917166, 0.822013, 1.10835, 1.14671, 0.949399,
-1.01348, 1.07893, 0.564832, 0.704571, 1.1337, 1.58693, 0.463972,
-0.734966, 0.897794, 1.30018, 0.909768, 0.640371, 0.541355, 0.685204,
-1.09255, 0.531485, 0.693595, 0.814454, 1.08119, 0.497489, 0.497872,
-0.822327, 0.4964, 0.566723, 0.606257, 0.711031, 0.683499, 1.26004,
-1.13398, 0.529169, 0.538057, 0.564507, 0.493755, 1.00047, 1.24981,
-0.973904, 0.859757, 0.462606, 0.588109, 0.691391, 0.666279, 0.927818,
-1.05845, 0.45543, 0.79399, 0.885761, 0.513252, 0.637226, 0.698318,
-0.404093, 0.979977, 1.42097, 0.761441, 1.0802, 2.09035, 2.85473,
-2.44305, 1.81988, 1.78082, 1.69385, 0.643862, 1.5311, 0.960032,
-0.69531, 0.821253, 0.49187, 0.394229, 0.806075, 0.557793, 0.694918,
-1.46079, 1.56847, 0.823876, 0.73726, 0.698766, 0.800476, 1.45114,
-1.15917, 0.692247, 0.610882, 0.709356, 0.630025, 0.81496, 2.35916,
-1.30581, 1.1819, 1.11921, 0.618407, 0.821751, 0.76678, 0.845531,
-0.519626, 0.636336, 0.82726, 0.896255, 0.786207, 0.959944, 0.528469,
-0.607334, 0.434402, 0.527194, 1.04028, 0.40121, 0.693556, 1.07389,
-1.40933, 0.702048), .Dim = c(200, 3), title = "Line example from BUGS manual", .Dimnames = list(
- c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11",
- "12", "13", "14", "15", "16", "17", "18", "19", "20", "21",
- "22", "23", "24", "25", "26", "27", "28", "29", "30", "31",
- "32", "33", "34", "35", "36", "37", "38", "39", "40", "41",
- "42", "43", "44", "45", "46", "47", "48", "49", "50", "51",
- "52", "53", "54", "55", "56", "57", "58", "59", "60", "61",
- "62", "63", "64", "65", "66", "67", "68", "69", "70", "71",
- "72", "73", "74", "75", "76", "77", "78", "79", "80", "81",
- "82", "83", "84", "85", "86", "87", "88", "89", "90", "91",
- "92", "93", "94", "95", "96", "97", "98", "99", "100", "101",
- "102", "103", "104", "105", "106", "107", "108", "109", "110",
- "111", "112", "113", "114", "115", "116", "117", "118", "119",
- "120", "121", "122", "123", "124", "125", "126", "127", "128",
- "129", "130", "131", "132", "133", "134", "135", "136", "137",
- "138", "139", "140", "141", "142", "143", "144", "145", "146",
- "147", "148", "149", "150", "151", "152", "153", "154", "155",
- "156", "157", "158", "159", "160", "161", "162", "163", "164",
- "165", "166", "167", "168", "169", "170", "171", "172", "173",
- "174", "175", "176", "177", "178", "179", "180", "181", "182",
- "183", "184", "185", "186", "187", "188", "189", "190", "191",
- "192", "193", "194", "195", "196", "197", "198", "199", "200"
- ), c("alpha", "beta", "sigma")), mcpar = c(1, 200, 1), class = "mcmc"),
- line2 = structure(c(2.0665, 2.55073, 3.72809, 2.90303, 3.06816,
- 2.98528, 2.3895, 3.34781, 2.72255, 3.03422, 2.63764, 3.06537,
- 2.81315, 2.81342, 3.29965, 3.34629, 2.49348, 3.10066, 3.36426,
- 3.12697, 3.34863, 3.10297, 3.74189, 2.83072, 2.9638, 2.79184,
- 3.32553, 2.68574, 3.27625, 3.34029, 3.02742, 2.65711, 3.84285,
- 1.96594, 3.97947, 2.29779, 2.84843, 3.13026, 2.90137, 2.99816,
- 3.11093, 2.90318, 3.45998, 3.13388, 3.07965, 3.18346, 2.24565,
- 3.16838, 3.20878, 2.97041, 2.03604, 1.92021, 3.88952, 2.55067,
- 3.21949, 3.14698, 3.05184, 2.87204, 3.32694, 3.26103, 3.57177,
- 3.91897, 4.0938, 2.88649, 2.22315, 3.23495, 3.14733, 3.32536,
- 2.39064, 2.84845, 2.92939, 2.7519, 2.95218, 3.2797, 3.18452,
- 2.25467, 3.0187, 3.139, 3.52716, 2.874, 3.15899, 3.32123,
- 2.88329, 2.81646, 2.65933, 3.35541, 2.77517, 2.72268, 3.23746,
- 2.95345, 3.31671, 3.03783, 3.17906, 2.68964, 2.90325, 3.1247,
- 3.29658, 2.17373, 3.20434, 2.73006, 3.07409, 3.16792, 3.15965,
- 2.92753, 2.12887, 2.3563, 3.34344, 3.06189, 3.18122, 2.88713,
- 3.28045, 3.10015, 3.00738, 3.02902, 2.77719, 3.27406, 2.93017,
- 1.78484, 2.30908, 3.26235, 1.69871, 2.17906, 4.32621, 1.92995,
- 4.06669, 3.20001, 2.57108, 3.02103, 3.15325, 3.27674, 2.0916,
- 2.09049, 3.31506, 3.65649, 2.70318, 2.81422, 3.24301, 2.97542,
- 3.30149, 2.28222, 3.0605, 2.92056, 3.04161, 3.08682, 2.67589,
- 3.05074, 2.65665, 2.76893, 3.19402, 2.64889, 3.52223, 3.4263,
- 2.66415, 3.14702, 3.22297, 2.72178, 3.26504, 3.1093, 3.09429,
- 3.0888, 2.73249, 2.4253, 3.11828, 3.42255, 3.3503, 3.19407,
- 3.29954, 3.2595, 2.88135, 2.64103, 2.73082, 2.79848, 3.84443,
- 3.88629, 3.05079, 2.82624, 3.18078, 2.32302, 2.64219, 2.68628,
- 3.10314, 0.995679, 3.86631, 3.17386, 3.4696, 2.47629, 2.91303,
- 3.31464, 3.17376, 3.48446, 2.39874, 2.9073, 3.51113, 3.25472,
- 3.2314, 3.40695, 3.07729, 3.1929, 3.16783, 3.04118, 0.94983,
- 0.533868, 0.520681, 0.976253, 0.936261, 0.663807, 0.520043,
- 0.944512, 1.05836, 0.829194, 0.427276, 1.00063, 1.0042, 0.676282,
- 0.724315, 0.378694, 0.854646, 0.816283, 0.680898, 0.729862,
- 0.466017, 0.474517, 0.394259, 0.643551, 1.41783, 0.83389,
- 0.770501, 0.60024, 0.931097, 1.03179, 0.520711, 0.576376,
- 0.757683, -0.0119585, 0.150777, 1.24154, 0.586833, 0.687874,
- 0.972612, 0.616836, 0.951993, 0.654136, 0.835886, 0.760564,
- 1.31897, 0.689678, 0.906503, 1.17308, 0.784572, 1.08129,
- 1.45739, 1.78349, 0.508111, 0.935584, 1.13076, 0.642275,
- 0.774581, 0.598707, 0.62828, 1.04412, 0.41416, 1.19133, 1.51109,
- 1.76453, 1.83201, 1.22612, 1.06988, 0.671452, 0.554991, 0.975127,
- 0.790377, 0.902487, 0.731783, 1.0601, 1.34457, 0.285294,
- 0.391361, 0.46474, 0.975072, 0.698322, 0.526451, 0.643863,
- 0.671277, 0.793108, 0.691103, 1.02774, 0.396104, 0.521036,
- 0.802256, 0.695039, 1.14746, 0.583661, 0.502895, 1.073, 0.48887,
- 0.622952, 0.652116, 0.925127, 0.563, 0.94581, 0.863503, 0.818531,
- 0.467898, 1.20696, 0.989445, 0.251698, 1.30748, 1.20417,
- 0.971032, 1.02162, 0.853551, 0.52759, 0.655414, 0.944856,
- 0.851747, 0.795153, 1.00725, 0.393811, 0.492267, 0.513625,
- 0.429794, 0.46022, 0.0291329, 1.29284, 0.965173, 0.986593,
- 0.884349, 0.450296, 0.979947, 1.03558, 1.19383, 0.00606791,
- 1.5062, 0.536381, 0.815264, 0.408098, 0.729014, 0.544239,
- 1.06494, 0.918886, 1.08346, 0.807998, 0.721469, 0.791212,
- 0.797347, 1.12917, 0.948997, 0.610172, 1.00315, 0.936662,
- 0.99261, 0.714404, 0.87753, 0.801131, 1.04282, 0.856488,
- 0.974811, 0.980089, 0.808844, 0.648608, 1.46944, 0.480841,
- 0.637054, 0.858352, 0.58538, 0.498672, 0.549712, 0.950073,
- 1.0674, 0.788781, 1.17857, 1.38812, 0.822348, 1.22831, 1.12554,
- 0.978673, 0.777699, 0.725505, 0.490426, 1.8001, -0.423911,
- 0.401579, 0.462218, 1.06891, 0.799904, 0.242961, 0.935728,
- 0.785555, 0.598434, 0.794666, 1.04866, 0.121866, 1.4973,
- 1.05516, 0.890826, 1.08431, 0.894609, 0.650802, 0.73541,
- 0.711719, 2.85379, 1.71367, 0.785154, 0.948167, 0.900588,
- 0.353863, 1.08933, 0.970812, 0.687744, 0.638359, 0.685602,
- 1.08756, 0.945919, 1.0119, 0.396287, 0.703951, 1.09031, 0.520708,
- 0.508404, 0.653224, 0.697648, 1.38661, 1.70559, 0.911467,
- 0.791402, 2.10078, 0.615926, 0.712817, 0.507729, 0.607383,
- 0.683574, 0.607109, 0.861146, 0.956142, 3.11952, 1.72381,
- 0.775019, 0.549051, 0.378787, 0.606155, 1.15792, 0.96476,
- 0.860189, 0.543162, 0.581212, 0.597179, 0.883207, 0.612349,
- 0.453471, 0.560563, 1.83515, 2.71558, 1.86329, 0.95504, 0.819032,
- 0.856319, 0.513872, 0.615228, 0.458746, 0.812665, 0.880437,
- 1.57162, 1.35811, 1.77924, 3.2142, 1.47968, 0.747181, 0.824633,
- 0.722867, 0.985975, 0.44006, 0.857335, 0.8669, 0.883645,
- 0.685724, 0.607935, 1.16049, 0.705714, 1.20252, 1.07224,
- 0.661277, 0.577825, 0.684492, 0.472472, 0.590746, 0.919054,
- 1.0548, 0.931485, 1.10547, 0.587061, 0.815852, 1.00739, 0.98054,
- 0.76707, 0.677419, 0.432805, 0.686665, 0.836332, 0.829481,
- 0.943772, 0.642839, 0.589167, 0.785612, 0.631841, 1.6026,
- 1.15419, 1.48332, 0.819761, 0.99212, 0.679848, 0.706879,
- 0.611507, 0.703271, 0.575749, 0.483907, 0.459734, 0.774127,
- 2.67997, 1.33679, 1.14551, 1.28857, 1.58951, 2.05222, 3.26272,
- 1.34444, 0.701195, 0.93947, 0.657195, 0.759601, 0.554493,
- 1.08315, 2.5578, 1.17271, 1.28146, 0.575432, 0.915557, 1.02713,
- 0.680568, 0.732328, 0.759689, 1.41759, 0.656574, 0.626601,
- 0.542805, 0.762587, 0.581579, 1.42557, 0.575034, 0.782904,
- 0.737252, 0.764629, 0.528021, 1.02315, 0.402441, 0.505607,
- 0.885029, 0.428758, 0.503349, 0.531532, 0.502562, 1.31589,
- 2.06585, 0.699819, 0.747237, 0.646591, 0.681749, 0.893148,
- 0.529854, 0.353713, 0.919825, 1.03411, 1.47011, 1.20727,
- 0.836974, 0.897857, 1.0101, 0.66153, 0.772771, 0.708564,
- 2.06246, 2.36283, 2.6266, 2.18514, 1.4795, 0.959802, 1.67397,
- 1.14405, 0.46466, 0.943977, 0.853832, 1.00929, 1.14416, 2.24906,
- 1.0981, 0.606293, 1.30693, 0.846828, 0.465129, 0.672417,
- 0.639787), .Dim = c(200, 3), title = "Line example from BUGS manual", .Dimnames = list(
- c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10",
- "11", "12", "13", "14", "15", "16", "17", "18", "19",
- "20", "21", "22", "23", "24", "25", "26", "27", "28",
- "29", "30", "31", "32", "33", "34", "35", "36", "37",
- "38", "39", "40", "41", "42", "43", "44", "45", "46",
- "47", "48", "49", "50", "51", "52", "53", "54", "55",
- "56", "57", "58", "59", "60", "61", "62", "63", "64",
- "65", "66", "67", "68", "69", "70", "71", "72", "73",
- "74", "75", "76", "77", "78", "79", "80", "81", "82",
- "83", "84", "85", "86", "87", "88", "89", "90", "91",
- "92", "93", "94", "95", "96", "97", "98", "99", "100",
- "101", "102", "103", "104", "105", "106", "107", "108",
- "109", "110", "111", "112", "113", "114", "115", "116",
- "117", "118", "119", "120", "121", "122", "123", "124",
- "125", "126", "127", "128", "129", "130", "131", "132",
- "133", "134", "135", "136", "137", "138", "139", "140",
- "141", "142", "143", "144", "145", "146", "147", "148",
- "149", "150", "151", "152", "153", "154", "155", "156",
- "157", "158", "159", "160", "161", "162", "163", "164",
- "165", "166", "167", "168", "169", "170", "171", "172",
- "173", "174", "175", "176", "177", "178", "179", "180",
- "181", "182", "183", "184", "185", "186", "187", "188",
- "189", "190", "191", "192", "193", "194", "195", "196",
- "197", "198", "199", "200"), c("alpha", "beta", "sigma"
- )), mcpar = c(1, 200, 1), class = "mcmc")), .Names = c("line1",
-"line2"), class = "mcmc.list")
diff --git a/data/line.rda b/data/line.rda
new file mode 100644
index 0000000..1ec0287
Binary files /dev/null and b/data/line.rda differ
diff --git a/inst/CITATION b/inst/CITATION
new file mode 100644
index 0000000..f9cb00f
--- /dev/null
+++ b/inst/CITATION
@@ -0,0 +1,17 @@
+citHeader("To cite package coda in publications use:")
+
+citEntry(entry="Article",
+ title = "CODA: Convergence Diagnosis and Output Analysis for MCMC",
+ author = personList(as.person("Martyn Plummer"),
+ as.person("Nicky Best"),
+ as.person("Kate Cowles"),
+ as.person("Karen Vines")),
+ journal = "R News",
+ year = 2006,
+ volume = 6,
+ number = 1,
+ pages = "7--11",
+ url = "http://CRAN.R-project.org/doc/Rnews/",
+ pdf = "http://CRAN.R-project.org/doc/Rnews/Rnews_2006-1.pdf",
+ textVersion = "Martyn Plummer, Nicky Best, Kate Cowles and Karen Vines (2006). CODA: Convergence Diagnosis and Output Analysis for MCMC, R News, vol 6, 7-11")
+
diff --git a/man/gelman.diag.Rd b/man/gelman.diag.Rd
index afa65d9..b8e4e1a 100644
--- a/man/gelman.diag.Rd
+++ b/man/gelman.diag.Rd
@@ -36,6 +36,18 @@ distribution of the variable under examination is normal. Hence the
`transform' parameter may be used to improve the normal approximation.
}
+\value{
+
+ An object of class \code{gelman.diag}. This is a list with the
+ following elements:
+ \item{psrf}{A list containing the point estimates of the potential
+ scale reduction factor (labelled \code{Point est.}) and their upper
+ confidence limits (labelled \code{Upper C.I.}).}
+ \item{mpsrf}{The point estimate of the multivariate potential scale reduction
+ factor. This is NULL if there is only one variable in \code{x}.}
+ The \code{gelman.diag} class has its own \code{print} method.
+}
+
\section{Theory}{
Gelman and Rubin (1992) propose a general approach to monitoring
@@ -85,7 +97,7 @@ factor if the MCMC run is continued.
\note{
The multivariate a version of Gelman and Rubin's diagnostic was
-proposed by Brooks and Gelman (1997). Unlike the univariate proportional
+proposed by Brooks and Gelman (1998). Unlike the univariate proportional
scale reduction factor, the multivariate version does not include an
adjustment for the estimated number of degrees of freedom.
}
@@ -94,7 +106,7 @@ adjustment for the estimated number of degrees of freedom.
Gelman, A and Rubin, DB (1992) Inference from iterative simulation
using multiple sequences, \emph{Statistical Science}, \bold{7}, 457-511.
-Brooks, SP. and Gelman, A. (1997) General methods for monitoring
+Brooks, SP. and Gelman, A. (1998) General methods for monitoring
convergence of iterative simulations. \emph{Journal of Computational and
Graphical Statistics}, \bold{7}, 434-455.
}
diff --git a/man/gelman.plot.Rd b/man/gelman.plot.Rd
index 262787e..0f9be1d 100644
--- a/man/gelman.plot.Rd
+++ b/man/gelman.plot.Rd
@@ -5,7 +5,7 @@
\usage{
gelman.plot(x, bin.width = 10, max.bins = 50,
-confidence = 0.95, transform = FALSE, auto.layout = TRUE,
+confidence = 0.95, transform = FALSE, autoburnin=TRUE, auto.layout = TRUE,
ask, col, lty, xlab, ylab, type, \dots)
}
@@ -16,6 +16,7 @@ ask, col, lty, xlab, ylab, type, \dots)
\item{max.bins}{Maximum number of bins, excluding the last one.}
\item{confidence}{Coverage probability of confidence interval.}
\item{transform}{Automatic variable transformation (see \code{gelman.diag})}
+ \item{autoburnin}{Remove first half of sequence (see \code{gelman.diag})}
\item{auto.layout}{If \code{TRUE} then, set up own layout for
plots, otherwise use existing one.}
\item{ask}{Prompt user before displaying each page of plots. Default is
@@ -43,8 +44,8 @@ the bin width, the third contains samples \eqn{1:(50+2n)} and so on.
\references{
Brooks, S P. and Gelman, A. (1998) General Methods for Monitoring
-Convergence of Iterative Simulations. Journal of Computational and
-Graphical Statistics. 7. p434-455.
+Convergence of Iterative Simulations. \emph{Journal of Computational and
+Graphical Statistics}, \bold{7}, 434-455.
}
\section{Theory}{
--
Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/debian-science/packages/r-cran-coda.git
More information about the debian-science-commits
mailing list