make.design {surveillance} | R Documentation |
Create the design matrices
Description
Creates the design matrices needed for meanResponse
Usage
make.design(disProgObj, control=list(lambda=TRUE, neighbours=FALSE,
linear=FALSE, nseason=0,
negbin=c("none", "single", "multiple"),
proportion=c("none", "single", "multiple")) )
Arguments
disProgObj |
Object of class disProg |
control |
Control object:
- lambda
- if
TRUE an autoregressive
parameter λ is included, if lambda is a vector of logicals,
unit-specific parameters λ_i are included
- neighbours
- if
TRUE an autoregressive parameter for
adjacent units phi is included, if neighbours is a vector of logicals,
unit-specific parameters phi_i are included
- linear
- a
logical (or a vector of logicals) indicating wether a linear
trend β (or a linear trend β_i for each unit)
is included
- nseason
- integer number of Fourier frequencies
nseason ; if nseason is a vector
of integers, each unit i gets its own seasonal parameters
- negbin
- if
"single" negative binomial rather than poisson is used,
if "multiple" unit-specific overdispersion parameters are used.
- proportion
- see details in
meanResponse
|
Value
list |
- Y
- matrix with number of cases y_it in unit i at
time t as elements, i.e. data without the first time point.
- Ym1
- matrix with previous number of cases y_i,t-1,
i.e data without the last time point.
- Ym1.neighbours
- matrix with weighted sum of earlier counts of adjacent units
sum_(j ~ i) w_ji * y_j,t-1
- nOfNeighbours
- vector with number of neighbours for each unit i
- X.trendSeason
- design matrix for linear trend and seasonal components
- populationFrac
- matrix with corresponding population proportions
- dimTheta
- list with number of parameters used in model
- control
- control object
- disProgObj
- Object of class
disProg
|
Author(s)
M.Paul, L. Held
[Package
surveillance version 0.9-7
Index]