Revision 600 trunk/contrib/statslib/dzinbinom.cpp

dzinbinom.cpp (revision 600)
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\brief Zero Inflated Negative binomial with size and mean
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\author Mollie Brooks
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\param x observed count. should be greater than or equal to 0.
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\param mu is the predicted mean
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\param mu is the mean of the negative binomial part
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\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
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\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.  
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\return negative log likelihood
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\return negative log-likelihood
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\ingroup STATLIB
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**/
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......
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\brief Zero Inflated Negative binomial with size and mean
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\author Mollie Brooks
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\param x observed count. should be greater than or equal to 0.
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\param mu is the predicted mean
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\param mu is the mean of the negative binomial part
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\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
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\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.  
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\return negative log likelihood
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\return negative log-likelihood
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\ingroup STATLIB
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**/
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......
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\brief Zero Inflated Negative binomial with size and mean
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\author Mollie Brooks
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\param x observed counts. should be greater than or equal to 0.
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\param mu is the predicted mean
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\param mu is the mean of the negative binomial part
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\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
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\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.  
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\return negative log likelihood
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\return negative log-likelihood
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\ingroup STATLIB
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**/
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......
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\brief Zero Inflated Negative binomial with size and mean
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\author Mollie Brooks
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\param x observed counts
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\param mu is the predicted mean
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\param mu is the mean of the negative binomial part
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\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
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\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.  
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\return negative log likelihood
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\return negative log-likelihood
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\ingroup STATLIB
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**/
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df1b2variable dzinbinom(const dvector& x, const df1b2vector& mu, const df1b2vector& k, const df1b2variable& p)
......
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\brief Zero Inflated Negative binomial with size and mean
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\author Mollie Brooks
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\param x observed counts
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\param mu is the predicted mean
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\param mu is the mean of the negative binomial part
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\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
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\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.  
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\return negative log likelihood
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\return negative log-likelihood
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\ingroup STATLIB
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**/
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dvariable dzinbinom(const dvector& x, const dvar_vector& mu, const prevariable& k, const prevariable& p)
......
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\brief Zero Inflated Negative binomial with size and mean
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\author Mollie Brooks
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\param x observed counts
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\param mu is the predicted mean
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\param mu is the mean of the negative binomial part
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\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
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\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.  
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\return negative log likelihood
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\return negative log-likelihood
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\ingroup STATLIB
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**/
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dvariable dzinbinom(const dvector& x, const dvar_vector& mu, const dvar_vector& k, const prevariable& p)
......
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\brief Zero Inflated Negative binomial with size and mean
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\author Mollie Brooks
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\param x observed counts
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\param mu is the predicted mean
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\param mu is the mean of the negative binomial part
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\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0
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\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.  
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\return negative log likelihood
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\return negative log-likelihood
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\ingroup STATLIB
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**/
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df1b2variable dzinbinom(const dvector& x, const df1b2vector& mu, const df1b2variable& k, const df1b2vector& p)
......
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\brief Zero Inflated Negative binomial with size and mean
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\author Mollie Brooks
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\param x observed counts
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\param mu is the predicted mean
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\param mu is the mean of the negative binomial part
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