wmmTree {AutoWMM} | R Documentation |
wmmTree
Description
Main function. Generate weighted estimates using the weighted multiplier method.
Usage
wmmTree(
tree,
sample_length = 10,
method = "mmEstimate",
int.type = "quants",
single.source = FALSE
)
Arguments
tree |
A makeTree object |
sample_length |
An integer for number of samples |
method |
Method specifying weighting. Only default compatible with 'mmEstimate' at this time |
int.type |
A string specifying interval type. Default "quants" generates the interval using the quantiles giving the central 95% of the samples. Alternatively, "var" can be used to generate a variance-weighted confidence interval, and "cox" generates a Cox interval. |
single.source |
Set to TRUE if all data comes from single, fully informed source. Default is FALSE. |
Value
Returns a makeTree object with branches and nodes now associated with estimates and samples generated with the weighted multiplier method
Examples
data(treeData1)
tree <- makeTree(treeData1)
Zhats <- wmmTree(tree, sample_length = 3)
message("Another example with a larger tree")
message("note - longer run time example")
data(treeData2)
tree2 <- makeTree(treeData2)
Zhats <- wmmTree(tree2, sample_length = 3)
Zhats$estimates # print the estimates of the root node generated by the 15 iterations
Zhats$weights # prints the weights of each branch
Zhats$root # prints the final estimate of the root node by WMM
Zhats$uncertainty # prints the final rounded estimate of the root with conf. int.
message(paste("show the average root estimate with 95% confidence interval,",
"as well as average estimates with confidence interval for each parameter"))
tree2$Get('uncertainty')
message("show the samples generated from each path which provides root estimates")
tree2$Get('targetEst_samples')
message("show the probabilities sampled at each branch leading into the given node")
tree2$Get('probability_samples')
[Package AutoWMM version 1.0.2 Index]