Description Usage Arguments Value Examples
Performs MEM test given the data for y and x on the null hypothesis H_0: m = m_0.
1 2 3 |
y |
n by 1 vector of data |
x |
n by q matrix of data for x (if exists) |
m |
The number of components in the mixture defined by a null hypothesis, m_0 |
z |
n by p matrix of regressor associated with gamma |
an |
a term used for penalty function |
tauset |
A set of initial tau value candidates |
ninits |
The number of randomly drawn initial values. |
crit.method |
Method used to compute the variance-covariance matrix, one of |
nbtsp |
The number of bootstrap observations; by default, it is set to be 199 |
cl |
Cluster used for parallelization; if it is |
parallel |
Determines whether package |
A list of class normalMix
with items:
coefficients |
A vector of parameter estimates. Ordered as α_1,…,α_m,μ_1,…,μ_m,σ_1,…,σ_m,\gam. |
parlist |
The parameter estimates as a list containing alpha, mu, and sigma (and gam if z is included in the model). |
vcov |
The estimated variance-covariance matrix. |
loglik |
The maximized value of the log-likelihood. |
penloglik |
The maximized value of the penalized log-likelihood. |
aic |
Akaike Information Criterion of the fitted model. |
bic |
Bayesian Information Criterion of the fitted model. |
postprobs |
n by m matrix of posterior probabilities for observations |
components |
n by 1 vector of integers that indicates the indices of components each observation belongs to based on computed posterior probabilities |
call |
The matched call. |
m |
The number of components in the mixture. |
1 2 3 4 | data(faithful)
attach(faithful)
normalmixMEMtest(y = eruptions, m = 1, crit.method = "asy")
normalmixMEMtest(y = eruptions, m = 2, crit.method = "asy")
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