| plaid.grid {biclust} | R Documentation |
Parameter Grid for BCPlaid Biclustering
Description
Generates a list containing parameter settings for the ensemble algorithm.
Usage
plaid.grid(method = "BCPlaid", cluster = "b", fit.model = y ~ m + a + b,
background = TRUE, background.layer = NA, background.df = 1,
row.release = c(0.5, 0.6, 0.7), col.release = c(0.5, 0.6, 0.7),
shuffle = 3, back.fit = 0, max.layers = 20, iter.startup = 5,
iter.layer = 10, verbose = FALSE)
Arguments
method |
Here BCPlaid, to perform Plaid algorithm |
cluster |
'r', 'c' or 'b', to cluster rows, columns or both (default 'b') |
fit.model |
Model (formula) to fit each layer. Usually, a linear model is used, that estimates three parameters: m (constant for all elements in the bicluster), a(contant for all rows in the bicluster) and b (constant for all columns). Thus, default is: y ~ m + a + b. |
background |
If 'TRUE' the method will consider that a background layer (constant for all rows and columns) is present in the data matrix. |
background.layer |
If background='TRUE' a own background layer (Matrix with dimension of x) can be specified. |
background.df |
Degrees of Freedom of backround layer if background.layer is specified. |
shuffle |
Before a layer is added, it's statistical significance is compared against a number of layers obtained by random defined by this parameter. Default is 3, higher numbers could affect time performance. |
iter.startup |
Number of iterations to find starting values |
iter.layer |
Number of iterations to find each layer |
back.fit |
After a layer is added, additional iterations can be done to refine the fitting of the layer (default set to 0) |
row.release |
Scalar in [0,1](with interval recommended [0.5-0.7]) used as threshold to prune rows in the layers depending on row homogeneity |
col.release |
As above, with columns |
max.layers |
Maximum number of layer to include in the model |
verbose |
If 'TRUE' prints extra information on progress. |
Value
A list containing parameter settings
Author(s)
Sebastian Kaiser sebastian.kaiser@stat.uni-muenchen.de
See Also
Examples
plaid.grid()