MixSim {MixSim} | R Documentation |
Generates a finite mixture model with Gaussian components for prespecified levels of maximum and/or average overlaps
MixSim(BarOmega = NULL, MaxOmega = NULL, K, p, sph = 0, ecc = 0.90, PiLow = 1.0, Ubound = 1.0, resN = 100, eps = 1e-06, acc = 1e-06, lim = 1e06)
BarOmega |
value of desired average overlap |
MaxOmega |
value of desired maximum overlap |
K |
number of components |
p |
number of dimensions |
sph |
covariance matrix structure (0 - nonspherical, 1 - spherical) |
ecc |
maximum eccentricity |
PiLow |
value of the smallest mixing proportion (if 'PiLow' is not reachable with respect to K, equal proportions are taken; PiLow = 1.0 implies equal proportions by default) |
Ubound |
upper bound for mean vectors; coordinates are simulated according to Uniform(0, Ubound) |
resN |
maximum number of dataset resimulations |
eps |
error bound for overlap computation |
acc |
error bound for integration (Davies, 1980) |
lim |
maximum number of integration terms (Davies, 1980) |
If 'BarOmega' is not specified, the function generates a mixture solely based on 'MaxOmega'; if 'MaxOmega' is not specified, the function generates a mixture solely based on 'BarOmega'.
Pi |
vector of mixing proprtions |
Mu |
matrix consisting of components' mean vectors (K x p) |
S |
set of components' covariance matrices (p x p x K) |
OmegaMap |
matrix of misclassification probabilities (K x K); OmegaMap[i,j] is the probability that X coming from the i-th component is classified to the j-th component |
BarOmega |
value of average overap |
MaxOmega |
value of maximum overap |
rcMax |
row and column numbers for the pair of components producing maximum overlap 'MaxOmega' |
fail |
flag value; 0 represents successful mixture generation, 1 represents failure |
Melnykov, V., Chen, W.-C., Maitra, R.
Maitra, R. and Melnykov, V. (200?) "Simulating data to study performance of finite mixture modeling and clustering algorithms", The Journal of Computational and Graphical Statistics.
Davies, R. (1980) "The distribution of a linear combination of chi-square random variables", Applied Statistics, 29, 323-333.
overlap, pdplot, simdataset
# controls average and maximum overlaps MixSim(BarOmega = 0.05, MaxOmega = 0.15, K = 4, p = 5) # controls average overlap MixSim(BarOmega = 0.05, , K = 4, p = 5) # controls maximum overlap MixSim( , MaxOmega = 0.15, K = 4, p = 5)