Description Usage Arguments Value Author(s) References See Also Examples
EM-test for the order of a finite mixture of Poissons.
1 2 | emtest.pois(x, m0 = 1, C = NULL,
inival = NULL, len = 10, niter = 50, tol = 1e-6, k = 3, rformat = FALSE)
|
x |
data, can be either a vector or a matrix with the 1st column being the observed values and the 2nd column being the corresponding frequencies. |
m0 |
order of the finite mixture model under the null hypothesis, default value: m0 = 1. |
C |
optional tuning parameter for EM-test procedure, default value: C = NULL. (if not provided, it will be determined by the formulas described in Chen and Li, 2011). |
inival |
initial values for the EM-algorithm to compute the MLE under the null model, a 2m0-dimension vector including m0 mixing proportions and m0 component parameters, or a matrix with 2m0 columns, default value: inival = NULL. (if not provided, random initial values are used.) |
len |
number of random initial values for the EM-algorithm, default value: len = 10. |
niter |
number of iterations for all initial values in the EM-algorithm. The algorithm runs EM-iteration niter times from each initial value. The iteration will restart from the parameter value with the highest likelihood value at the point and run until convergence. default value: niter = 50. |
tol |
tolerance level for the convergence of the EM-algorithm, default value: tol = 1e-6. |
k |
number of EM iterations: default value: k = 3. |
rformat |
form of the digital output: default of R package is used when rformat = T; If rformat = T, the digital output is rounded to the 3rd dicimal place if it is larger than 0.001, keeps 3 significant digits otherwise. The default value of rformat is F. |
Return an object of class EM-test with the following elements:
MLE of the parameters under the null hypothesis (order = m0)
Parameter estimates under the specific alternative whose order is 2m0.
EM-test statistic
P-value
Level of penalty
Shaoting Li, Jiahua Chen and Pengfei Li
Chen, J. and Li, P. (2011). Tuning the EM-test for the order of finite mixture models. The Canadian Journal of Statistics. 39, 389–404.
Li, P. and Chen, J. (2010). Testing the order of a finite mixture model. JASA. 105, 1084–1092.
Li, P., Chen, J. and Marriott, P. (2009). Non-finite Fisher information and homogeneity: The EM approach. Biometrika. 96, 411–426.
plotmix.pois, pmle.pois, rmix.pois
1 2 3 4 | #load the earthquake data set,
#conduct homogeneity test by the EM-test.
data(earthquake)
emtest.pois(earthquake,2)
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