ADMB Documentation  11.1.2192
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Files | Functions
Statistical Fuctions.
User-Contributed Libraries.

Files

file  baranov.cpp
 

Routines for iteratively solving the Baranov catch equation.


file  dbeta.cpp
 

Beta density functions.


file  dbinom.cpp
 

Binomial density functions.


file  dgamma.cpp
 

Gamma density functions.


file  dinvgamma.cpp
 

Inverse gamma distribution.


file  dlnorm.cpp
 

Lognormal density functions.


file  dmultinom.cpp
 

Multinomial distribution.


file  dmvlogistic.cpp
 

Multivariate logistic negative log likelihood.


file  dnorm.cpp
 

Normal density functions.


file  dpois.cpp
 

Poisson density functions.


file  dunif.cpp
 

Uniform distribution.


file  eplogis.cpp
 

// Exponential logistic


file  fill.cpp
 

Fills a matrix with a vector

This function fills a matrix m with a vector v.


file  multifan.cpp
 

/Robust normal approximation to the multinomial distribution


file  pearsonresiduals.cpp
 

// Pearson residuals


file  rmvlogistic.cpp
 

Random multivariate logistic negative log likelihood.


file  statsLib.h
 

Library of statistic functions.


file  studentT.cpp
 

Student T density functions.


file  vcubicspline.cpp
 

Cubic spline functions.


Functions

dvar_matrix ageLengthKey (const dvar_vector &mu, const dvar_vector &sig, const dvector &x)
 Age Length Key.
dvariable dnbinom (const double &x, const prevariable &mu, const prevariable &k)
 negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k
df1b2variable dnbinom (const double &x, const df1b2variable &mu, const df1b2variable &k)
 negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k
df1b2variable dnbinom (const dvector &x, const df1b2vector &mu, const df1b2variable &k)
 negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k
df1b2variable dnbinom (const dvector &x, const df1b2vector &mu, const df1b2vector &k)
 negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k
dvariable dnbinom (const dvector &x, const dvar_vector &mu, const prevariable &k)
 negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k
dvariable dnbinom (const dvector &x, const dvar_vector &mu, const dvar_vector &k)
 negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k
dvariable dnbinom_tau (const double &x, const prevariable &mu, const prevariable &tau)
 negative log likelihood of negative binomial with mean and tau
df1b2variable dnbinom_tau (const double &x, const df1b2variable &mu, const df1b2variable &tau)
 negative log likelihood of negative binomial with mean and tau
df1b2variable dnbinom_tau (const dvector &x, const df1b2vector &mu, const df1b2variable &tau)
 negative log likelihood of negative binomial with mean and tau
df1b2variable dnbinom_tau (const dvector &x, const df1b2vector &mu, const df1b2vector &tau)
 negative log likelihood of negative binomial with mean and tau
dvariable dnbinom_tau (const dvector &x, const dvar_vector &mu, const prevariable &tau)
 negative log likelihood of negative binomial with mean and tau
dvariable dnbinom_tau (const dvector &x, const dvar_vector &mu, const dvar_vector &tau)
 negative log likelihood of negative binomial with mean and tau
df1b2variable dzinbinom (const double &x, const df1b2variable &mu, const df1b2variable &k, const df1b2variable &p)
 ecologically parametarized negative binomial with zero inflation
dvariable dzinbinom (const double &x, const prevariable &mu, const prevariable &k, const prevariable &p)
 ecologically parametarized negative binomial with zero inflation
df1b2variable dzinbinom (const dvector &x, const df1b2vector &mu, const df1b2variable &k, const df1b2variable &p)
 ecologically parametarized negative binomial with zero inflation
df1b2variable dzinbinom (const dvector &x, const df1b2vector &mu, const df1b2vector &k, const df1b2variable &p)
 ecologically parametarized negative binomial with zero inflation
dvariable dzinbinom (const dvector &x, const dvar_vector &mu, const prevariable &k, const prevariable &p)
 ecologically parametarized negative binomial with zero inflation
dvariable dzinbinom (const dvector &x, const dvar_vector &mu, const dvar_vector &k, const prevariable &p)
 ecologically parametarized negative binomial with zero inflation
df1b2variable dzinbinom (const dvector &x, const df1b2vector &mu, const df1b2variable &k, const df1b2vector &p)
 now p is a vector///
df1b2variable dzinbinom (const dvector &x, const df1b2vector &mu, const df1b2vector &k, const df1b2vector &p)
 ecologically parametarized negative binomial with zero inflation
dvariable dzinbinom (const dvector &x, const dvar_vector &mu, const prevariable &k, const dvar_vector &p)
 ecologically parametarized negative binomial with zero inflation
dvariable dzinbinom (const dvector &x, const dvar_vector &mu, const dvar_vector &k, const dvar_vector &p)
 ecologically parametarized negative binomial with zero inflation

Detailed Description

Contributed by Steven Martell.


Function Documentation

dvar_matrix ageLengthKey ( const dvar_vector mu,
const dvar_vector sig,
const dvector x 
)

Age Length Key.

Author:
Steven James Dean Martell UBC Fisheries Centre
Date:
2011-06-28
Parameters:
muis the mean length-at-age
sigis the std in mean length-at-age
xis the vector of break points for the length bins
Returns:
dvar_matrix containing the probability of length(x) for a given age(a)
See also:

Definition at line 41 of file alk.cpp.

dvariable dnbinom ( const double &  x,
const prevariable mu,
const prevariable k 
)

negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k

Negative binomial with mean and quadratic variance

Author:
Steven Martell and Mollie Brooks
Parameters:
xobserved count
muis the predicted mean
kis the overdispersion parameter, i.e. shape parameter of underlying gamma heterogeneity (different from tau). should be >0
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$

Definition at line 12 of file dnbinom.cpp.

df1b2variable dnbinom ( const double &  x,
const df1b2variable mu,
const df1b2variable k 
)

negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k

Negative binomial with mean and quadratic variance

Author:
Mollie Brooks
Parameters:
xobserved count
muis the predicted mean
kis the overdispersion parameter, i.e. shape parameter of underlying gamma heterogeneity (different from tau). should be >0
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$

Definition at line 40 of file dnbinom.cpp.

df1b2variable dnbinom ( const dvector x,
const df1b2vector mu,
const df1b2variable k 
)

negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k

Negative binomial with mean and quadratic variance

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the predicted mean
kis the overdispersion parameter, i.e. shape parameter of underlying gamma heterogeneity (different from tau). should be >0
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$

Definition at line 67 of file dnbinom.cpp.

df1b2variable dnbinom ( const dvector x,
const df1b2vector mu,
const df1b2vector k 
)

negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k

Negative binomial with mean and quadratic variance

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the predicted mean
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying gamma heterogeneity (different from tau). should be >0
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$

Definition at line 99 of file dnbinom.cpp.

dvariable dnbinom ( const dvector x,
const dvar_vector mu,
const prevariable k 
)

negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k

Negative binomial with mean and quadratic variance

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the predicted mean
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying gamma heterogeneity (different from tau). should be >0
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$

Definition at line 134 of file dnbinom.cpp.

dvariable dnbinom ( const dvector x,
const dvar_vector mu,
const dvar_vector k 
)

negative log likelihood of negative binomial with mean=mu and variance = mu + mu^2 /k

Negative binomial with mean and quadratic variance

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the predicted mean
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying gamma heterogeneity (different from tau). should be >0
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$

Definition at line 166 of file dnbinom.cpp.

dvariable dnbinom_tau ( const double &  x,
const prevariable mu,
const prevariable tau 
)

negative log likelihood of negative binomial with mean and tau

Negative binomial with mean=mu and variance = mu*tau

Author:
Mollie Brooks
Parameters:
xobserved count
muis the predicted mean
tauis the overdispersion parameter like in the quasi-poisson. should be >1
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$ where $ k=\mu/(10^{-120}+\tau-1.0) $

Definition at line 16 of file dnbinom_tau.cpp.

df1b2variable dnbinom_tau ( const double &  x,
const df1b2variable mu,
const df1b2variable tau 
)

negative log likelihood of negative binomial with mean and tau

Negative binomial with mean=mu and variance = mu*tau

Author:
Mollie Brooks
Parameters:
xobserved count
muis the predicted mean
tauis the overdispersion parameter like in the quasi-poisson. should be >1
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$ where $ k=\mu/(10^{-120}+\tau-1.0) $

Definition at line 45 of file dnbinom_tau.cpp.

df1b2variable dnbinom_tau ( const dvector x,
const df1b2vector mu,
const df1b2variable tau 
)

negative log likelihood of negative binomial with mean and tau

Negative binomial with mean=mu and variance = mu*tau

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the predicted mean
tauis the overdispersion parameter like in the quasi-poisson. should be >1
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$ where $ k=\mu/(10^{-120}+\tau-1.0) $

Definition at line 73 of file dnbinom_tau.cpp.

df1b2variable dnbinom_tau ( const dvector x,
const df1b2vector mu,
const df1b2vector tau 
)

negative log likelihood of negative binomial with mean and tau

Negative binomial with mean=mu and variance = mu*tau

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the predicted mean
tauis the overdispersion parameter like in the quasi-poisson. should be >1
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$ where $ k=\mu/(10^{-120}+\tau-1.0) $

Definition at line 106 of file dnbinom_tau.cpp.

dvariable dnbinom_tau ( const dvector x,
const dvar_vector mu,
const prevariable tau 
)

negative log likelihood of negative binomial with mean and tau

Negative binomial with mean=mu and variance = mu*tau

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the predicted mean
tauis the overdispersion parameter like in the quasi-poisson. should be >1
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$ where $ k=\mu/(10^{-120}+\tau-1.0) $

Definition at line 142 of file dnbinom_tau.cpp.

dvariable dnbinom_tau ( const dvector x,
const dvar_vector mu,
const dvar_vector tau 
)

negative log likelihood of negative binomial with mean and tau

Negative binomial with mean=mu and variance = mu*tau

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the predicted mean
tauis the overdispersion parameter like in the quasi-poisson. should be >1
Returns:
negative log likelihood $ -( \ln(\Gamma(x+k))-\ln(\Gamma(k))-\ln(x!)+k\ln(k)+x\ln(\mu)-(k+x)\ln(k+\mu) )$ where $ k=\mu/(10^{-120}+\tau-1.0) $

Definition at line 175 of file dnbinom_tau.cpp.

df1b2variable dzinbinom ( const double &  x,
const df1b2variable mu,
const df1b2variable k,
const df1b2variable p 
)

ecologically parametarized negative binomial with zero inflation

Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved count. should be greater than or equal to 0.
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 20 of file dzinbinom.cpp.

dvariable dzinbinom ( const double &  x,
const prevariable mu,
const prevariable k,
const prevariable p 
)

ecologically parametarized negative binomial with zero inflation

Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved count. should be greater than or equal to 0.
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 57 of file dzinbinom.cpp.

df1b2variable dzinbinom ( const dvector x,
const df1b2vector mu,
const df1b2variable k,
const df1b2variable p 
)

ecologically parametarized negative binomial with zero inflation

Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved counts. should be greater than or equal to 0.
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 92 of file dzinbinom.cpp.

df1b2variable dzinbinom ( const dvector x,
const df1b2vector mu,
const df1b2vector k,
const df1b2variable p 
)

ecologically parametarized negative binomial with zero inflation

Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 133 of file dzinbinom.cpp.

dvariable dzinbinom ( const dvector x,
const dvar_vector mu,
const prevariable k,
const prevariable p 
)

ecologically parametarized negative binomial with zero inflation

Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 175 of file dzinbinom.cpp.

dvariable dzinbinom ( const dvector x,
const dvar_vector mu,
const dvar_vector k,
const prevariable p 
)

ecologically parametarized negative binomial with zero inflation

Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 216 of file dzinbinom.cpp.

df1b2variable dzinbinom ( const dvector x,
const df1b2vector mu,
const df1b2variable k,
const df1b2vector p 
)

now p is a vector///

ecologically parametarized negative binomial with zero inflation Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 261 of file dzinbinom.cpp.

df1b2variable dzinbinom ( const dvector x,
const df1b2vector mu,
const df1b2vector k,
const df1b2vector p 
)

ecologically parametarized negative binomial with zero inflation

Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 302 of file dzinbinom.cpp.

dvariable dzinbinom ( const dvector x,
const dvar_vector mu,
const prevariable k,
const dvar_vector p 
)

ecologically parametarized negative binomial with zero inflation

Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 344 of file dzinbinom.cpp.

dvariable dzinbinom ( const dvector x,
const dvar_vector mu,
const dvar_vector k,
const dvar_vector p 
)

ecologically parametarized negative binomial with zero inflation

Zero Inflated Negative binomial with size and mean

Author:
Mollie Brooks
Parameters:
xobserved counts
muis the mean of the negative binomial part
kis the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
pis the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.
Returns:
negative log-likelihood

Definition at line 385 of file dzinbinom.cpp.