Description Usage Arguments Value References See Also Examples
Computes piecewise constant maximum likelihood estimators with minimal number of jumps under given restrictions on subintervals.
Deprecation warning: This function is a help function for smuceR
and jsmurf
and may be removed when these function will be removed.
1 2 3 4 5 6 7 8  stepbound(y, bounds, ...)
## Default S3 method:
stepbound(y, bounds, x = 1:length(y), x0 = 2 * x[1]  x[2],
max.cand = NULL, family = c("gauss", "gaussvar", "poisson", "binomial", "gaussKern"),
param = NULL, weights = rep(1, length(y)), refit = y,
jumpint = confband, confband = FALSE, ...)
## S3 method for class 'stepcand'
stepbound(y, bounds, refit = TRUE, ...)

y 
a vector of numerical observations 
bounds 
bounds on the value allowed on intervals; typically computed with 
x 
a numeric vector of the same length as 
x0 
a single numeric giving the last unobserved sample point directly before sampling started 
max.cand, weights 
see 
family, param 
specifies distribution of data, see family 
refit 

jumpint 

confband 

... 
arguments to be passed to generic methods 
An object of class stepfit
that contains the fit; if jumpint == TRUE
function jumpint
allows to extract the confidence interval for the jumps, if confband == TRUE
function confband
allows to extract the confidence band.
Frick, K., Munk, A., and Sieling, H. (2014) Multiscale changepoint inference. With discussion and rejoinder by the authors. Journal of the Royal Statistical Society, Series B 76(3), 495–580.
Hotz, T., Schütte, O., Sieling, H., Polupanow, T., Diederichsen, U., Steinem, C., and Munk, A. (2013) Idealizing ion channel recordings by a jump segmentation multiresolution filter. IEEE Transactions on NanoBioscience 12(4), 376–386.
bounds
, smuceR
, jsmurf
, stepsel
, stepfit
, jumpint
, confband
1 2 3 4 5 6 7 8 9 10 11 12  # simulate poisson data with two levels
y < rpois(100, c(rep(1, 50), rep(4, 50)))
# compute bounds
b < bounds(y, penalty="len", family="poisson", q=4)
# fit step function to bounds
sb < stepbound(y, b, family="poisson", confband=TRUE)
plot(y)
lines(sb)
# plot confidence intervals for jumps on axis
points(jumpint(sb), col="blue")
# confidence band
lines(confband(sb), lty=2, col="blue")

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