mapfit.point {mapfit} | R Documentation |
MAP fitting with point data
Description
Estimates MAP parameters from point data.
Usage
mapfit.point(map, x, intervals, ...)
Arguments
map |
An object for MAP. The estimation algorithm is selected depending on this class. |
x |
A vector for point data. |
intervals |
A vector for intervals. |
... |
Further options for fitting methods. |
Value
Returns a list with components, which is an object of S3 class mapfit.result
;
model |
an object for estimated PH class. |
llf |
a value of the maximum log-likelihood. |
df |
a value of degrees of freedom of the model. |
aic |
a value of Akaike information criterion. |
iter |
the number of iterations. |
convergence |
a logical value for the convergence of estimation algorithm. |
ctime |
computation time (user time). |
data |
an object for data class |
aerror |
a value of absolute error for llf at the last step of algorithm. |
rerror |
a value of relative error for llf at the last step of algorithm. |
options |
a list of options used for fitting. |
call |
the matched call. |
Examples
## load trace data
data(BCpAug89)
BCpAug89s <- head(BCpAug89, 50)
## MAP fitting for general MAP
(result1 <- mapfit.point(map=map(2), x=cumsum(BCpAug89s)))
## MAP fitting for MMPP
(result2 <- mapfit.point(map=mmpp(2), x=cumsum(BCpAug89s)))
## MAP fitting for ER-HMM
(result3 <- mapfit.point(map=erhmm(3), x=cumsum(BCpAug89s)))
## marginal moments for estimated MAP
map.mmoment(k=3, map=result1$model)
map.mmoment(k=3, map=result2$model)
map.mmoment(k=3, map=result3$model)
## joint moments for estimated MAP
map.jmoment(lag=1, map=result1$model)
map.jmoment(lag=1, map=result2$model)
map.jmoment(lag=1, map=result3$model)
## lag-k correlation
map.acf(map=result1$model)
map.acf(map=result2$model)
map.acf(map=result3$model)