Type: | Package |
Title: | Generalized Hermite Distribution |
Version: | 1.1.2 |
Date: | 2018-05-17 |
Encoding: | UTF-8 |
Author: | David Moriña, Manuel Higueras, Pedro Puig and María Oliveira |
Maintainer: | David Moriña Soler <david.morina@uab.cat> |
Description: | Probability functions and other utilities for the generalized Hermite distribution. |
Depends: | R (≥ 2.15.0), maxLik |
Repository: | CRAN |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
Packaged: | 2018-05-17 08:54:42 UTC; 47642555X |
Date/Publication: | 2018-05-17 13:33:53 UTC |
Generalized Hermite distribution
Description
Probability mass, distribution and quantile functions; random generation; and regression models for the generalized Hermite distribution.
Details
Package: | hermite |
Type: | Package |
Version: | 1.1.2 |
Date: | 2018-05-17 |
License: | GPL version 2 or newer |
LazyLoad: | yes |
The package implements probability mass function dhermite
,
distribution function phermite
, quantile function
qhermite
and random generation rhermite
for the
generalized Hermite distribution. The probability mass function is usually
parametrized in terms of the mean \mu
and the index of dispersion
d = \frac{\sigma^2}{\mu}
:
P(X=x) = P(X=0) \frac{\mu^x (m-d)^x}{(m-1)^x} \sum_{j=0}^{[x/m]}
\frac{(d-1)^j (m-1)^{(m-1)j}}{m^j \mu^{(m-1)j} (m-d)^{mj} (x-mj)!j!}
where P(X=0) = exp(\mu (-1+ \frac{d-1}{m}))
, m
is the degree of
the generalized Poisson distribution and [x/m]
is the integer part of
x/m
.
The package is able to fit Hermite regression models as well, by means of the
function glm.hermite
, also in the presence of covariates.
Author(s)
David Moriña, Manuel Higueras, Pedro Puig and María Oliveira
Mantainer: David Moriña Soler <david.morina@uab.cat>
References
Kemp C D, Kemp A W. Some Properties of the Hermite Distribution. Biometrika 1965;52 (3-4):381–394.
McKendrick A G Applications of Mathematics to Medical Problems. Proceedings of the Edinburgh Mathematical Society 1926;44:98–130.
Kemp A W, Kemp C D. An alternative derivation of the Hermite distribution. Biometrika 1966;53 (3-4):627–628.
Patel Y C. Even Point Estimation and Moment Estimation in Hermite Distribution. Biometrics 1976;32 (4):865–873.
Gupta R P, Jain G C. A Generalized Hermite distribution and Its Properties. SIAM Journal on Applied Mathematics 1974;27:359–363.
Bekelis, D. Convolutions of the Poisson laws in number theory. In Analytic & Probabilistic Methods in Number Theory: Proceedings of the 2nd International Conference in Honour of J. Kubilius, Lithuania 1996;4:283–296.
Zhang J, Huang H. On Nonnegative Integer-Valued Lévy Processes and Applications in Probabilistic Number Theory and Inventory Policies. American Journal of Theoretical and Applied Statistics 2013;2:110–121.
Kotz S. Encyclopedia of statistical sciences. John Wiley 1982-1989.
Kotz S. Univariate discrete distributions. Norman L. Johnson 2005.
Puig P. (2003). Characterizing Additively Closed Discrete Models by a Property of Their Maximum Likelihood Estimators, with an Application to Generalized Hermite Distributions. Journal of the American Statistical Association 2003; 98:687–692.
See Also
Distributions
for some other distributions,
qhermite
, phermite
, rhermite
,
hermite-package
, glm.hermite
Probability mass function for the generalized Hermite distribution
Description
Probability mass function for the generalized Hermite distribution with
parameters a
, b
and m
.
Usage
dhermite(x, a, b, m=2)
Arguments
x |
vector of non-negative integer quantiles. |
a |
first parameter for the Hermite distribution. |
b |
second parameter for the Hermite distribution. |
m |
degree of the generalized Hermite distribution. Its default value is |
Value
Probability for a generalized Hermite random varible with parameters a
,
b
and m
of taking x
counts.
Author(s)
David Moriña, Manuel Higueras, Pedro Puig and María Oliveira
References
Kemp C D, Kemp A W. Some Properties of the Hermite Distribution. Biometrika 1965;52 (3-4):381–394.
McKendrick A G Applications of Mathematics to Medical Problems. Proceedings of the Edinburgh Mathematical Society 1926;44:98–130.
Kemp A W, Kemp C D. An alternative derivation of the Hermite distribution. Biometrika 1966;53 (3-4):627–628.
Patel Y C. Even Point Estimation and Moment Estimation in Hermite Distribution. Biometrics 1976;32 (4):865–873.
Gupta R P, Jain G C. A Generalized Hermite distribution and Its Properties. SIAM Journal on Applied Mathematics 1974;27:359–363.
Bekelis, D. Convolutions of the Poisson laws in number theory. In Analytic & Probabilistic Methods in Number Theory: Proceedings of the 2nd International Conference in Honour of J. Kubilius, Lithuania 1996;4:283–296.
Zhang J, Huang H. On Nonnegative Integer-Valued Lévy Processes and Applications in Probabilistic Number Theory and Inventory Policies. American Journal of Theoretical and Applied Statistics 2013;2:110–121.
Kotz S. Encyclopedia of statistical sciences. John Wiley 1982-1989.
Kotz S. Univariate discrete distributions. Norman L. Johnson 2005.
Puig P. (2003). Characterizing Additively Closed Discrete Models by a Property of Their Maximum Likelihood Estimators, with an Application to Generalized Hermite Distributions. Journal of the American Statistical Association 2003; 98:687–692.
See Also
Distributions
for some other distributions,
qhermite
, phermite
, rhermite
,
hermite-package
, glm.hermite
Examples
d <- dhermite(3, 0.8, 0.3)
Maximum likelihood estimation and Hermite regression
Description
glm.hermite
is used to fit generalized linear models with count
responses following a Hermite distribution, specified by giving a symbolic
description of the linear predictor. A summary
method providing the
most meaningful information on the fitted model is available for objects of
class glm.hermite
.
Usage
glm.hermite(formula, data, link="log", start=NULL, m = NULL)
Arguments
formula |
symbolic description of the model. A typical predictor has the form
|
data |
an optional data frame containing the variables in the model. |
link |
character specification of link function: "log" or "identity". By default
|
start |
a vector containing the starting values for the parameters of the specified
model. Its default value is |
m |
value for parameter |
Value
glm.hermite
returns an object of class glm.hermite
, which is a
list including the following components:
coefs the vector of coefficients.
data an optional data frame containing the variables in the model.
loglik log-likelihood of the fitted model.
vcov covariance matrix of all coefficients in the model (derived from the Hessian of the
maxLik
output).hessHessian matrix, returned by the
maxLik
output.fitted.values the fitted mean values, obtained by transforming the linear predictors by the inverse of the link function.
wLikelihood ratio test statistic.
pvalLikelihood ratio test p-value.
Author(s)
María Oliveira, Manuel Higueras, David Moriña and Pere Puig
References
Kemp C D, Kemp A W. Some Properties of the Hermite Distribution. Biometrika 1965;52 (3-4):381–394.
McKendrick A G Applications of Mathematics to Medical Problems. Proceedings of the Edinburgh Mathematical Society 1926;44:98–130.
Kemp A W, Kemp C D. An alternative derivation of the Hermite distribution. Biometrika 1966;53 (3-4):627–628.
Patel Y C. Even Point Estimation and Moment Estimation in Hermite Distribution. Biometrics 1976;32 (4):865–873.
Gupta R P, Jain G C. A Generalized Hermite distribution and Its Properties. SIAM Journal on Applied Mathematics 1974;27:359–363.
Bekelis, D. Convolutions of the Poisson laws in number theory. In Analytic & Probabilistic Methods in Number Theory: Proceedings of the 2nd International Conference in Honour of J. Kubilius, Lithuania 1996;4:283–296.
Zhang J, Huang H. On Nonnegative Integer-Valued Lévy Processes and Applications in Probabilistic Number Theory and Inventory Policies. American Journal of Theoretical and Applied Statistics 2013;2:110–121.
Kotz S. Encyclopedia of statistical sciences. John Wiley 1982-1989.
Kotz S. Univariate discrete distributions. Norman L. Johnson 2005.
Puig P. (2003). Characterizing Additively Closed Discrete Models by a Property of Their Maximum Likelihood Estimators, with an Application to Generalized Hermite Distributions. Journal of the American Statistical Association 2003; 98:687–692.
See Also
Distributions
for some other distributions,
qhermite
, phermite
, rhermite
,
hermite-package
Examples
data <- c(rep(0,122), rep(1,40), rep(2,14), rep(3,16), rep(4,6), rep(5,2))
mle1 <- glm.hermite(data~1, link="log", start=NULL, m=3)
mle1
Internal hermite functions
Description
Internal hermite functions
Usage
int.hermite(x, a, b, m)
edg(y, a, b, m=2)
cofi(p, a, b, m=2)
## S3 method for class 'glm.hermite'
summary(object, ...)
## S3 method for class 'glm.hermite'
print.summary(x, ...)
Details
These functions are not to be called by the user
See Also
hermite-package
, dhermite
, phermite
,
qhermite
, rhermite
, glm.hermite
High-LET Radiation Exposure
Description
This data corresponds to an experimental simulation of in vitro whole body irradiation for high-LET radiation exposure, where peripheral blood samples were exposed to 10 different doses of 1480MeV oxygen ions. For each dose, the number of dicentrics chromosomes per blood cell were scored.
Usage
hi_let
Format
A data frame with 7413 rows and 3 columns.
Source
DiGiorgio M. et al. (2004) Chromosome aberrations induced in human lymphocytes by heavycharged particles in track segment mode. Radiation Protection Dosimetry, 108, 47-53.
References
DiGiorgio M., Edwards A. A., Moquet J. E., Finnon P., Hone P. A., Lloyd D. C., Kreiner A. J., Schuff J. A., Taja M. R., Vallerga M. B., López F. O. and Burlón A., Debray M. E., Valda A. (2004) Chromosome aberrations induced in human lymphocytes by heavycharged particles in track segment mode. Radiation Protection Dosimetry, 108, 47-53.
Hot 100 hits
Description
This data corresponds to the 965 "number 1" hits on the Hot 100 chart over the period January 1955 to December 2003. For a recording that reaches the number one spot, Weeks measures the number of weeks that it stays at number one. The covariates are: Elvis = 1 if the recording was by Elvis Presley, = 0 otherwise; Beatles = 1 if the recording was by the Beatles, = 0 otherwise; Group = 1 if the recording was by a band, = 0 otherwise; Female = 1 if the artist was a solo female, = 0 otherwise; Male = 1 if the artist was a solo male, = 0 otherwise; Inst = 1 if the recording was purely instrumental, = 0 otherwise; and NonCon = 1 if the recording topped the charts in nonconsecutive weeks, = 0 otherwise.
Usage
hot100
Format
A data frame with 965 rows and 9 columns.
Source
http://web.uvic.ca/~dgiles/downloads/data/hot100.xls
References
Giles, D. E. (2006) Superstardom in the US popular music industry revisited. Economics Letters, 92(1):68–74. Giles, D. E. (2007) Modeling inflated count data. In Y. Berbers and W. Zwaenepoel, editors, Proceedings of the MODSIM 2007 International Congress on Modelling and Simulation, pages 919–925. L. Oxley and D. Kulasiri, Eds., Modelling and Simulation Society of Australia and New Zealand
Distribution function for the generalized Hermite distribution
Description
Distribution function for the generalized Hermite distribution with
parameters a
, b
and m
.
Usage
phermite(q, a, b, m=2, lower.tail=TRUE)
Arguments
q |
vector of non-negative integer quantiles. |
a |
first parameter for the Hermite distribution. |
b |
second parameter for the Hermite distribution. |
m |
degree of the generalized Hermite distribution. Its default value is |
lower.tail |
logical; if TRUE (default), probabilities are |
Value
Probability for a generalized Hermite random varible with parameters a
,
b and m
to be lower (or greater) than q
.
Author(s)
David Moriña, Manuel Higueras, Pedro Puig and María Oliveira
References
Kemp C D, Kemp A W. Some Properties of the Hermite Distribution. Biometrika 1965;52 (3-4):381–394.
McKendrick A G Applications of Mathematics to Medical Problems. Proceedings of the Edinburgh Mathematical Society 1926;44:98–130.
Kemp A W, Kemp C D. An alternative derivation of the Hermite distribution. Biometrika 1966;53 (3-4):627–628.
Patel Y C. Even Point Estimation and Moment Estimation in Hermite Distribution. Biometrics 1976;32 (4):865–873.
Gupta R P, Jain G C. A Generalized Hermite distribution and Its Properties. SIAM Journal on Applied Mathematics 1974;27:359–363.
Bekelis, D. Convolutions of the Poisson laws in number theory. In Analytic & Probabilistic Methods in Number Theory: Proceedings of the 2nd International Conference in Honour of J. Kubilius, Lithuania 1996;4:283–296.
Zhang J, Huang H. On Nonnegative Integer-Valued Lévy Processes and Applications in Probabilistic Number Theory and Inventory Policies. American Journal of Theoretical and Applied Statistics 2013;2:110–121.
Kotz S. Encyclopedia of statistical sciences. John Wiley 1982-1989.
Kotz S. Univariate discrete distributions. Norman L. Johnson 2005.
Puig P. (2003). Characterizing Additively Closed Discrete Models by a Property of Their Maximum Likelihood Estimators, with an Application to Generalized Hermite Distributions. Journal of the American Statistical Association 2003; 98:687–692.
See Also
Distributions
for some other distributions,
dhermite
, qhermite
, rhermite
,
hermite-package
, glm.hermite
Examples
d <- phermite(4, 0.8, 0.3, m=3)
Quantile function for the generalized Hermite distribution
Description
Quantile function for the generalized Hermite distribution with parameters
a
, b
and m
.
Usage
qhermite(p, a, b, m=2, lower.tail=TRUE)
Arguments
p |
vector of probabilities. |
a |
first parameter for the Hermite distribution. |
b |
second parameter for the Hermite distribution. |
m |
degree of the generalized Hermite distribution. Its default value is |
lower.tail |
logical; if TRUE (default), probabilities are |
Value
The smallest integer x
such that
P(X \le x) \ge p
(or such that P(X \le x) \ge 1-p
if lower.tail
is set to FALSE
), where X is a generalized Hermite random variable with
parameters a
, b
and m
.
Author(s)
David Moriña, Manuel Higueras, Pedro Puig and María Oliveira
References
Kemp C D, Kemp A W. Some Properties of the Hermite Distribution. Biometrika 1965;52 (3-4):381–394.
McKendrick A G Applications of Mathematics to Medical Problems. Proceedings of the Edinburgh Mathematical Society 1926;44:98–130.
Kemp A W, Kemp C D. An alternative derivation of the Hermite distribution. Biometrika 1966;53 (3-4):627–628.
Patel Y C. Even Point Estimation and Moment Estimation in Hermite Distribution. Biometrics 1976;32 (4):865–873.
Gupta R P, Jain G C. A Generalized Hermite distribution and Its Properties. SIAM Journal on Applied Mathematics 1974;27:359–363.
Bekelis, D. Convolutions of the Poisson laws in number theory. In Analytic & Probabilistic Methods in Number Theory: Proceedings of the 2nd International Conference in Honour of J. Kubilius, Lithuania 1996;4:283–296.
Zhang J, Huang H. On Nonnegative Integer-Valued Lévy Processes and Applications in Probabilistic Number Theory and Inventory Policies. American Journal of Theoretical and Applied Statistics 2013;2:110–121.
Kotz S. Encyclopedia of statistical sciences. John Wiley 1982-1989.
Kotz S. Univariate discrete distributions. Norman L. Johnson 2005.
Puig P. (2003). Characterizing Additively Closed Discrete Models by a Property of Their Maximum Likelihood Estimators, with an Application to Generalized Hermite Distributions. Journal of the American Statistical Association 2003; 98:687–692.
See Also
Distributions
for some other distributions,
dhermite
, phermite
, rhermite
,
hermite-package
, glm.hermite
Examples
d <- qhermite(0.9999987, 0.8, 0.3, m=3)
Random generation for the generalized Hermite distribution
Description
Random generation for the generalized Hermite distribution with parameters
a
, b
and m
.
Usage
rhermite(n, a, b, m=2)
Arguments
n |
number of observations. |
a |
first parameter for the Hermite distribution. |
b |
second parameter for the Hermite distribution. |
m |
degree of the generalized Hermite distribution. Its default value is |
Value
A vector containing n
random deviates from a generalized Hermite
distribution.
Author(s)
David Moriña, Manuel Higueras, Pedro Puig and María Oliveira
References
Kemp C D, Kemp A W. Some Properties of the Hermite Distribution. Biometrika 1965;52 (3-4):381–394.
McKendrick A G Applications of Mathematics to Medical Problems. Proceedings of the Edinburgh Mathematical Society 1926;44:98–130.
Kemp A W, Kemp C D. An alternative derivation of the Hermite distribution. Biometrika 1966;53 (3-4):627–628.
Patel Y C. Even Point Estimation and Moment Estimation in Hermite Distribution. Biometrics 1976;32 (4):865–873.
Gupta R P, Jain G C. A Generalized Hermite distribution and Its Properties. SIAM Journal on Applied Mathematics 1974;27:359–363.
Bekelis, D. Convolutions of the Poisson laws in number theory. In Analytic & Probabilistic Methods in Number Theory: Proceedings of the 2nd International Conference in Honour of J. Kubilius, Lithuania 1996;4:283–296.
Zhang J, Huang H. On Nonnegative Integer-Valued Lévy Processes and Applications in Probabilistic Number Theory and Inventory Policies. American Journal of Theoretical and Applied Statistics 2013;2:110–121.
Kotz S. Encyclopedia of statistical sciences. John Wiley 1982-1989.
Kotz S. Univariate discrete distributions. Norman L. Johnson 2005.
Puig P. (2003). Characterizing Additively Closed Discrete Models by a Property of Their Maximum Likelihood Estimators, with an Application to Generalized Hermite Distributions. Journal of the American Statistical Association 2003; 98:687–692.
See Also
Distributions
for some other distributions,
dhermite
, phermite
, qhermite
,
hermite-package
, glm.hermite
Examples
rnd <- rhermite(1000, 0.8, 0.3)