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
|
BayesMDei2 <- function(formula, data, total, lambda1 = 4, lambda2 = 2,
tune.alpha = NULL, tune.beta = NULL,
start.alphas = NULL, start.betas = NULL,
sample = 1000,
thin = 1, burnin = 1000, verbose = 0, ret.beta =
'r', ret.mcmc = TRUE, usrfun = NULL, ...){
if(thin < 1){stop('thin must be positive integer')}
if(sample < 1){stop('thin must be positive integer')}
if(burnin < 0){stop('burnin must be non-negative integer')}
DD <- model.frame(formula, data)
countParty <- countGroup <- propParty <- propGroup <- FALSE
checkGroups <- round(apply(DD[[2]], 1, sum), 3)
checkParties <- round(apply(DD[[1]], 1, sum), 3)
if(all(DD[[1]] %% 1 == 0) & all(DD[[1]] >= 0)){countParty <- TRUE}
else if(all(0 <= DD[[1]] & DD[[1]] <= 1)){
if(all(checkParties == 1)){propParty <- TRUE}else{
stop("column marginals are proportions that do not
sum to 1 - please respecify data")}}
else stop("column marginals are neither counts nor proportions - please
respecify data")
if(all(DD[[2]] %% 1 == 0) & all(DD[[2]] >= 0)){countGroup <- TRUE}
else if(all(0 <= DD[[2]] & DD[[2]] <= 1)){
if(all(checkGroups == 1)){propGroup <- TRUE}else{
stop("row marginals are proportions that do not sum to 1 - please
respecify data")}}
else stop("row marginals are neither counts nor proportions - please
respecify data")
if((propParty | propGroup) & is.null(total)){
stop("one or both marginals are proportions - 'total' must be
provided")}
if(propParty & !is.null(total)){
DD[[1]] <- DD[[1]] * total
warning("column margnials are proportions - multiplying by unit size")}
if(propGroup & !is.null(total)){
DD[[2]] <- DD[[2]] * total
warning("row margnials are proportions - multiplying by unit size")}
checkGroups <- round(apply(DD[[2]], 1, sum), 1)
checkParties <- round(apply(DD[[1]], 1, sum), 1)
if(identical(checkParties, checkGroups) == FALSE){
stop("row and column totals unequal in some units - please
respecify data")}
Groups <- DD[[2]]
TT <- t(DD[[1]])
XX <- t(Groups/apply(Groups,1,sum))
group.names <- colnames(Groups)
party.names <- rownames(TT)
RR <- t(Groups)
NG <- nrow(XX)
NP <- nrow(TT)
Precincts <- nrow(DD)
usrenv <- environment(fun = usrfun)
if(is.null(start.alphas)){
start.alphas <- matrix(rgamma(NG*NP, lambda1, lambda2), NG, NP)}
if(min(start.alphas) <= 0){stop("inadmissable starting values for alpha")}
if(is.null(start.betas)){
start.betas <- array(NA, dim= c(NG, NP, Precincts))
for(i in 1:Precincts){
start.betas[,,i] <- rdirichlet(NG, rep(1,NP))}
}
if(identical(round(apply(start.betas, c(1,3), sum),10),matrix(1,NG,
Precincts))!=TRUE){stop("inadmissable
starting values
for beta")}
usrlen <- length(as.numeric(usrfun(list(start.alphas, start.betas, TT,
RR))))
if(is.null(tune.alpha)){
tune.alpha <- matrix(rep(.25,NG*NP), NG, NP)}
if(is.null(tune.beta)){
tune.beta <- array(rep(.05, NG*(NP-1)*Precincts), c(NG, NP-1, Precincts))}
tune.alpha <- as.matrix(tune.alpha)
if(identical(dim(tune.alpha), c(NG, NP))!=TRUE) {stop("'tune.alpha'
has incorrect dimensions")}
if(identical(as.numeric(dim(tune.beta)), c(NG, NP-1, Precincts))!=TRUE)
{stop("'tune.beta'
has incorrect dimensions")}
beta.names <- paste(paste(paste(group.names,matrix(rep(party.names,
NG),NG,NP, byrow=T)
,sep="."),
matrix(rep(1:Precincts,NG*NP),NG*NP, Precincts,
byrow=TRUE),sep="."), ".txt.gz", sep="")
if(ret.beta == 's'){touch.betas(beta.names)
ret.beta <- 2}
if(ret.beta == 'd'){ret.beta <- 1}
if(ret.beta == 'r'){ret.beta <- 0}
if(is.numeric(ret.beta)==FALSE){stop('incorrect option for
ret.beta')}
output <- .Call("rbycei_fcn2",
as.numeric(start.alphas),
as.numeric(start.betas),
as.numeric(TT),
as.numeric(XX),
as.numeric(tune.alpha),
as.numeric(tune.beta),
as.integer(NG),
as.integer(NP),
as.integer(Precincts),
as.numeric(lambda1),
as.numeric(lambda2),
as.integer(sample),
as.integer(thin),
as.integer(burnin),
as.integer(verbose),
as.integer(ret.beta),
as.numeric(RR),
usrfun,
usrenv,
as.integer(usrlen),
as.character(beta.names)
)
if(ret.beta==0){names(output) <- c("Alpha", "Beta", "alpha.acc",
"beta.acc", "cell.count", "usrfun")}
else{names(output) <- c("Alpha", "alpha.acc",
"beta.acc","cell.count", "usrfun")}
if(ret.mcmc){
colnames(output$Alpha) <- paste("alpha",matrix(rep(group.names,
NP),NG,NP)
,matrix(rep(party.names, NG),NG,NP,
byrow=T) ,sep=".")
output$Alpha <- coda::mcmc(output$Alpha, thin=thin)
colnames(output$cell.count) <- paste("ccount",matrix(rep(group.names,
NP),NG,NP)
,matrix(rep(party.names, NG),NG,NP,
byrow=T) ,sep=".")
output$cell.count <- coda::mcmc(output$cell.count, thin=thin)
colnames(output$usrfun) <- paste("usrfun", 1:ncol(output$usrfun), sep=".")
output$usrfun <- coda::mcmc(output$usrfun, thin=thin)
if(ret.beta==0){
colnames(output$Beta) <- paste(paste("beta", group.names,matrix(rep(party.names, NG),NG,NP, byrow=T) ,sep="."), matrix(rep(1:Precincts,NG*NP),NG*NP, Precincts, byrow=TRUE),sep=".")
output$Beta <- coda::mcmc(output$Beta, thin=thin)
}
}else{
output$Alpha <- array(t(output$Alpha), c(NG, NP, sample))
dimnames(output$Alpha) <- list(group.names, party.names, 1:sample)
output$cell.count <- array(t(output$cell.count), c(NG, NP, sample))
dimnames(output$cell.count) <- list(group.names, party.names,
1:sample)
colnames(output$usrfun) <- paste("usrfun", 1:ncol(output$usrfun), sep=".")
if(ret.beta==0){
output$Beta <- array(t(output$Beta), c(NG, NP, Precincts, sample))
dimnames(output$Beta) <- list(group.names, party.names, 1:Precincts,
1:sample)
}
}
return(output)
}
|
