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R/contacts.R
In panelPomp: Inference for Panel Partially Observed Markov Processes
Defines functions
contacts
Documented in
contacts
##' Contacts model
##'
##' A panel model for dynamic variation in sexual contacts, with
##' data from Vittinghof et al (1999). The model was developed by
##' Romero-Severson et al (2015) and discussed by \Breto et al (2020).
##'
##' @param params parameter vector.
##' @return
##' A \code{panelPomp} object.
##'
##' @author Edward L. Ionides
##'
##' @examples
##' \donttest{
##' contacts()
##' }
##' @export
##'
##' @references \breto2020
##'
##' \romeroseverson2015
##'
##' \vittinghoff1999
##' @family panelPomp examples
contacts <- function(params=c(mu_X=1.75,sigma_X=2.67,mu_D=3.81,
sigma_D=4.42,mu_R=0.04,sigma_R=0,alpha=0.90)){
contact_data <- read.table(
text = '"y1" "y2" "y3" "y4" "individual"
5 0 0 0 1
2 2 31 4 2
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31 1 0 0 188
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1 5 2 0 795
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17 1 1 1 821
0 0 0 0 822
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67 16 28 2 824
0 0 0 0 825
0 2 0 2 826
0 0 25 12 827
10 6 3 6 828
4 0 4 0 829
214 0 2 0 830
3 2 0 1 831
3 2 4 1 832
1 0 0 1 833
7 4 3 7 834
4 4 42 18 835
8 5 10 37 836
2 0 25 0 837
3 3 1 8 838
0 0 0 3 839
120 221 5 98 840
0 2 20 2 841
10 43 80 32 842
8 5 0 0 843
2 1 6 6 844
8 1 3 3 845
1 0 0 0 846
208 0 0 0 847
13 8 5 23 848
1 15 3 0 849
19 6 7 4 850
3 1 2 2 851
0 1 0 0 852
1 2 0 0 853
3 0 4 5 854
9 38 17 12 855
0 0 2 2 856
8 13 33 22 857
0 0 4 6 858
1 0 1 0 859
0 0 1 3 860
10 5 1 0 861
13 0 0 0 862
7 2 0 2 863
15 121 4 0 864
5 14 14 2 865
6 0 0 0 866
3 3 1 1 867
1 2 1 0 868
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20 27 5 20 870
4 10 4 2 871
0 0 1 6 872
82 20 0 0 873
0 0 0 7 874
26 2 0 6 875
2 0 0 0 876
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0 0 3 3 878
0 2 0 0 879
7 76 86 103 880
6 3 3 1 881
0 0 0 0 882',
header = TRUE
)
dmeas <- Csnippet("lik = dnbinom(y, D, D/(D+C), give_log);")
rmeas <- Csnippet("y = rnbinom(D, D/(D+C));")
rinit <- Csnippet("
double tol=0.000001;
D = (sigma_D < tol || mu_D < tol) ? mu_D :
rgamma(pow(mu_D/sigma_D,2), pow(sigma_D,2)/mu_D);
if(D < tol) {D = tol;}
R = (sigma_R < tol || mu_R < tol) ? mu_R :
rgamma(pow(mu_R/sigma_R, 2), pow(sigma_R, 2)/mu_R);
X = (sigma_X < tol || mu_X < tol) ? mu_X :
rgamma(pow(mu_X/sigma_X, 2), pow(sigma_X, 2)/mu_X);
Z = (R < tol) ? 1/tol : rexp(1/R);
C = 0;
")
rproc <- Csnippet("
double Zcum, tol=0.000001;
C = 0;
Zcum = Z;
while(Zcum < 6){ // time in months within a 6 month observation interval
C += Z * X;
Z = (R < tol) ? 1/tol : rexp(1/R);
X = (sigma_X < tol || mu_X < tol) ? mu_X :
rgamma(pow(mu_X/sigma_X, 2), pow(sigma_X, 2)/mu_X);
Zcum += Z;
}
C += (6 - (Zcum - Z)) * X;
C *= pow(alpha, (int)t % 4);
Z = Zcum - 6;
")
# check for existing 'cdir' (to make 'testthat' package work)
cdir <- if (exists("cdir",inherits=FALSE)) cdir else NULL
template <- pomp(data=data.frame(t=1:4,y=NA),
times="t",
t0=0,
rprocess=discrete_time(step.fun=rproc,delta.t=1),
rmeasure=rmeas,
dmeasure=dmeas,
params=params,
paramnames=c("mu_X","sigma_X","mu_D","sigma_D","mu_R","sigma_R","alpha"),
statenames=c("X","D","R","C","Z"),
obsnames="y",
partrans=parameter_trans(
log=c("mu_X","sigma_X","mu_D","sigma_D"),
logit="alpha"
),
rinit=rinit,
cdir=cdir
)
## build list of pomps
U <- nrow(contact_data)
poList <- setNames(vector(mode="list",length=U),
nm=paste0("unit",1:U))
for (u in seq_len(U)) {
poList[[u]] <- template
data_u <- pomp(
data.frame(t=time(template),y=as.numeric(contact_data[u,time(template)])),
times="t",
t0=timezero(template)
)
poList[[u]]@data <- data_u@data
}
## Construct panelPomp
panelPomp(object=poList,shared=coef(template))
}
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panelPomp documentation built on April 11, 2025, 6:18 p.m.
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Defines functions contacts
Documented in contacts
##' Contacts model
##'
##' A panel model for dynamic variation in sexual contacts, with
##' data from Vittinghof et al (1999). The model was developed by
##' Romero-Severson et al (2015) and discussed by \Breto et al (2020).
##'
##' @param params parameter vector.
##' @return
##' A \code{panelPomp} object.
##'
##' @author Edward L. Ionides
##'
##' @examples
##' \donttest{
##' contacts()
##' }
##' @export
##'
##' @references \breto2020
##'
##' \romeroseverson2015
##'
##' \vittinghoff1999
##' @family panelPomp examples
contacts <- function(params=c(mu_X=1.75,sigma_X=2.67,mu_D=3.81,
sigma_D=4.42,mu_R=0.04,sigma_R=0,alpha=0.90)){
contact_data <- read.table(
text = '"y1" "y2" "y3" "y4" "individual"
5 0 0 0 1
2 2 31 4 2
9 2 0 0 3
12 8 10 6 4
0 10 4 1 5
25 23 15 2 6
12 6 0 0 7
10 2 0 4 8
31 58 24 48 9
0 0 0 0 10
32 42 9 1 11
5 4 12 2 12
0 1 0 1 13
2 0 3 0 14
1 3 0 0 15
92 40 7 5 16
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214 0 2 0 830
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1 0 0 1 833
7 4 3 7 834
4 4 42 18 835
8 5 10 37 836
2 0 25 0 837
3 3 1 8 838
0 0 0 3 839
120 221 5 98 840
0 2 20 2 841
10 43 80 32 842
8 5 0 0 843
2 1 6 6 844
8 1 3 3 845
1 0 0 0 846
208 0 0 0 847
13 8 5 23 848
1 15 3 0 849
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0 1 0 0 852
1 2 0 0 853
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0 0 2 2 856
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0 0 4 6 858
1 0 1 0 859
0 0 1 3 860
10 5 1 0 861
13 0 0 0 862
7 2 0 2 863
15 121 4 0 864
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6 0 0 0 866
3 3 1 1 867
1 2 1 0 868
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4 10 4 2 871
0 0 1 6 872
82 20 0 0 873
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16 40 20 12 877
0 0 3 3 878
0 2 0 0 879
7 76 86 103 880
6 3 3 1 881
0 0 0 0 882',
header = TRUE
)
dmeas <- Csnippet("lik = dnbinom(y, D, D/(D+C), give_log);")
rmeas <- Csnippet("y = rnbinom(D, D/(D+C));")
rinit <- Csnippet("
double tol=0.000001;
D = (sigma_D < tol || mu_D < tol) ? mu_D :
rgamma(pow(mu_D/sigma_D,2), pow(sigma_D,2)/mu_D);
if(D < tol) {D = tol;}
R = (sigma_R < tol || mu_R < tol) ? mu_R :
rgamma(pow(mu_R/sigma_R, 2), pow(sigma_R, 2)/mu_R);
X = (sigma_X < tol || mu_X < tol) ? mu_X :
rgamma(pow(mu_X/sigma_X, 2), pow(sigma_X, 2)/mu_X);
Z = (R < tol) ? 1/tol : rexp(1/R);
C = 0;
")
rproc <- Csnippet("
double Zcum, tol=0.000001;
C = 0;
Zcum = Z;
while(Zcum < 6){ // time in months within a 6 month observation interval
C += Z * X;
Z = (R < tol) ? 1/tol : rexp(1/R);
X = (sigma_X < tol || mu_X < tol) ? mu_X :
rgamma(pow(mu_X/sigma_X, 2), pow(sigma_X, 2)/mu_X);
Zcum += Z;
}
C += (6 - (Zcum - Z)) * X;
C *= pow(alpha, (int)t % 4);
Z = Zcum - 6;
")
# check for existing 'cdir' (to make 'testthat' package work)
cdir <- if (exists("cdir",inherits=FALSE)) cdir else NULL
template <- pomp(data=data.frame(t=1:4,y=NA),
times="t",
t0=0,
rprocess=discrete_time(step.fun=rproc,delta.t=1),
rmeasure=rmeas,
dmeasure=dmeas,
params=params,
paramnames=c("mu_X","sigma_X","mu_D","sigma_D","mu_R","sigma_R","alpha"),
statenames=c("X","D","R","C","Z"),
obsnames="y",
partrans=parameter_trans(
log=c("mu_X","sigma_X","mu_D","sigma_D"),
logit="alpha"
),
rinit=rinit,
cdir=cdir
)
## build list of pomps
U <- nrow(contact_data)
poList <- setNames(vector(mode="list",length=U),
nm=paste0("unit",1:U))
for (u in seq_len(U)) {
poList[[u]] <- template
data_u <- pomp(
data.frame(t=time(template),y=as.numeric(contact_data[u,time(template)])),
times="t",
t0=timezero(template)
)
poList[[u]]@data <- data_u@data
}
## Construct panelPomp
panelPomp(object=poList,shared=coef(template))
}
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