Description Usage Arguments Details Value See Also Examples
A parameter frame is a data.frame where the rows correspond to different parameter specifications. The columns are divided into three parts. (1) the meta-information columns (e.g. index, value, constraint, etc.), (2) the attributes of an objective function (e.g. data contribution and prior contribution) and (3) the parameters.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
x |
data.frame. |
parameters |
character vector, the names of the parameter columns. |
metanames |
character vector, the names of the meta-information columns. |
obj.attributes |
character vector, the names of the objective function attributes. |
i |
row index in any format |
j |
column index in any format |
drop |
logical. If TRUE the result is coerced to the lowest possible dimension |
... |
additional arguments |
Parameter frames can be subsetted either by [ , ]
or by subset
. If
[ , index]
is used, the names of the removed columns will also be removed from
the corresponding attributes, i.e. metanames, obj.attributes and parameters.
An object of class parframe
, i.e. a data.frame with attributes for the
different names. Inherits from data.frame.
profile, mstrust
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 | ## Generate a prediction function
regfn <- c(y = "sin(a*time)")
g <- Y(regfn, parameters = "a")
x <- Xt(condition = "C1")
## Generate data
data <- datalist(
C1 = data.frame(
name = "y",
time = 1:5,
value = sin(1:5) + rnorm(5, 0, .1),
sigma = .1
)
)
## Initialize parameters and time
pars <- c(a = 1)
times <- seq(0, 5, .1)
plot((g*x)(times, pars), data)
## Do many fits from random positions and store them into parlist
out <- as.parlist(lapply(1:50, function(i) {
trust(normL2(data, g*x), pars + rnorm(length(pars), 0, 1), rinit = 1, rmax = 10)
}))
summary(out)
## Reduce parlist to parframe
parframe <- as.parframe(out)
plotValues(parframe)
## Reduce parframe to best fit
bestfit <- as.parvec(parframe)
plot((g*x)(times, bestfit), data)
|
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