Description Usage Arguments Value See Also
Completes algorithm, entropy, and spectrum control lists.
1 2 3 4 5 6 7 8 9  complete_algorithm_control(algorithm.control = list(max.iter = 50, num.starts
= 10, tol = 0.001, type = "EM"))
complete_entropy_control(entropy.control = list(base = NULL, method = "MLE",
prior.probs = NULL, prior.weight = 0.001, threshold = 0), num.outcomes)
complete_spectrum_control(spectrum.control = list(kernel = NULL, method =
c("wosa", "direct", "multitaper", "mvspec", "ar", "pgram"), smoothing =
FALSE))

algorithm.control 
list; control parameters for any iterative ForeCA algorithm. 
entropy.control 
list; control settings for entropy estimation. 
num.outcomes 
positive integer; number of outcomes for the discrete probability distribution. Must be specified (no default value). 
spectrum.control 
list; control settings for spectrum estimation. 
A list with fully specified algorithm, entropy, or spectrum controls.
Default values are only added if the input {spectrum,entropy,algorithm}.control
list does not already set this value.
complete_algorithm_control
returns a list containing:
max.iter 
maximum number of iterations; default: 
num.starts 
number of random starts to avoid local optima; default: 
tol 
tolerance for when convergence is reached in any iterative
ForeCA algorithm; default: 
type 
string; type of algorithm. Default: 
complete_entropy_control
returns a list with:
base 
logarithm base for the entropy. 
method 
string; method to estimate entropy; default: 
prior.probs 
prior distribution; default: uniform

prior.weight 
weight of the prior distribution; default: 
threshold 
nonnegative float; set probabilities below threshold to
zero; default: 
complete_spectrum_control
returns a list containing:
kernel 
R function; function to weigh each Fourier frequency λ;
default: 
method 
string; method to estimate the spectrum; default:

smoothing 
logical; default: 
Available methods for spectrum estimation are (alphabetical order)
"ar" 
autoregressive spectrum fit via 
"direct" 
raw periodogram using 
"multitaper" 
tapering the periodogram using 
"mvspec" 
smoothed estimate using 
"pgram" 
uses 
"wosa" 
Welch overlapping segment averaging (WOSA) using 
Setting smoothing = TRUE
will smooth the estimated spectrum
(again); this option is only available for univariate time series/spectra.
mvspectrum
, discrete_entropy
,
continuous_entropy
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