Description Usage Arguments Value References See Also Examples
Find a set of overlapping component distributions that gives the best fit to grouped data and conditional data, using a combination of a Newton-type method and EM algorithm.
1 2 3 4 |
mixdat |
A data frame containing grouped data, whose first column should be right boundaries of grouping intervals where the first and last intervals are open-ended; whose second column should consist of the frequencies indicating numbers of observations falling into each interval. If conditional data are available, this data frame should have k + 2 columns, where k is the number of components, whose element in row j and column i + 2 is the number of observations from the jth interval belonging to the ith component. |
mixpar |
A data frame containing starting values for parameters of component distributions, which are, in order, the proportions, means, and standard deviations. |
dist |
the distribution of components, it can be one of
|
constr |
a list of constraints on parameters of
component distributions. See function |
emsteps |
a non-negative integer specifying the number of EM steps to be performed. |
usecondit |
logical. If |
exptol |
a positive scalar giving the tolerance at which the scaled fitted value is considered large enough to be a degree of freedom. |
print.level |
this argument determines the level of printing
which is done during the optimization process. The default
value of |
... |
additional arguments to the optimization function
|
.
A list containing the following items:
parameters |
A data frame containing estimated values for parameters of component distributions, which are, in order, the proportions, means, and standard deviations. |
se |
A data frame containing estimated values for standard errors of parameters of component distributions. |
distribution |
the distribution used to fit the data. |
constraint |
the constraints on parameters. |
chisq |
the goodness-of-fit chi-square statistic. |
df |
degrees of freedom of the fitted mixture model. |
P |
a significance level (P-value) for the goodness-of-fit test. |
vmat |
covariance matrix for the estimated parameters. |
mixdata |
the original data, i.e. the argument |
usecondit |
the value of the argument |
Macdonald, P.D.M. and Green, P.E.J. (1988) User's Guide to Program MIX: An Interactive Program for Fitting Mixtures of Distributions. ICHTHUS DATA SYSTEMS.
mixgroup
for grouping data, mixparam
for
organizing the parameter values, mixconstr
for
constructing constraints. nlm
for additional
arguments.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | data(pike65)
data(pikepar)
fitpike1 <- mix(pike65, pikepar, "lnorm", constr = mixconstr(consigma = "CCV"), emsteps = 3)
fitpike1
plot(fitpike1)
data(pike65sg)
fitpike2 <- mix(pike65sg, pikepar, "lnorm", emsteps = 3, usecondit = TRUE)
fitpike2
plot(fitpike2)
data(bindat)
data(binpar)
fitbin1 <- mix(bindat, binpar, "binom",
constr = mixconstr(consigma = "BINOM", size = c(20, 20, 20, 20)))
plot(fitbin1)
fitbin2 <- mix(bindat, binpar, "binom", constr = mixconstr(conpi = "PFX",
fixpi = c(TRUE, TRUE, TRUE, TRUE),
consigma = "BINOM", size = c(20, 20, 20, 20)))
plot(fitbin2)
|
Parameters:
pi mu sigma
1 0.09967 23.07 2.372
2 0.51889 33.61 3.455
3 0.22677 41.10 4.226
4 0.10710 49.88 5.128
5 0.04757 60.47 6.217
Distribution:
[1] "lnorm"
Constraints:
conpi conmu consigma
"NONE" "NONE" "CCV"
Warning message:
In mix(pike65sg, pikepar, "lnorm", emsteps = 3, usecondit = TRUE) :
The optimization process terminated because iteration limit exceeded
Parameters:
pi mu sigma
1 0.10523 23.35 2.592
2 0.39080 32.78 2.991
3 0.38524 40.11 4.885
4 0.07370 51.69 4.341
5 0.04503 60.98 6.169
Distribution:
[1] "lnorm"
Constraints:
conpi conmu consigma
"NONE" "NONE" "NONE"
Warning messages:
1: In sqrt(mu - mu^2/constr$size) : NaNs produced
2: In sqrt(mu - mu^2/constr$size) : NaNs produced
Warning message:
In sqrt(mu - mu^2/constr$size) : NaNs produced
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