14 
14 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

15 
15 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

16 
16 
\return negative log likelihood


17 
\ingroup STATLIB

17 
18 
**/

18 
19 

19 
20 
df1b2variable dzinbinom(const double& x, const df1b2variable& mu, const df1b2variable& k, const df1b2variable& p)

...  ...  
50 
51 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

51 
52 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

52 
53 
\return negative log likelihood


54 
\ingroup STATLIB

53 
55 
**/

54 
56 

55 
57 
dvariable dzinbinom(const double& x, const prevariable& mu, const prevariable& k, const prevariable& p)

...  ...  
84 
86 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

85 
87 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

86 
88 
\return negative log likelihood


89 
\ingroup STATLIB

87 
90 
**/

88 
91 

89 
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df1b2variable dzinbinom(const dvector& x, const df1b2vector& mu, const df1b2variable& k, const df1b2variable& p)

...  ...  
125 
128 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

126 
129 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

127 
130 
\return negative log likelihood


131 
\ingroup STATLIB

128 
132 
**/

129 
133 
df1b2variable dzinbinom(const dvector& x, const df1b2vector& mu, const df1b2vector& k, const df1b2variable& p)

130 
134 
{

...  ...  
166 
170 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

167 
171 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

168 
172 
\return negative log likelihood


173 
\ingroup STATLIB

169 
174 
**/

170 
175 
dvariable dzinbinom(const dvector& x, const dvar_vector& mu, const prevariable& k, const prevariable& p)

171 
176 
{

...  ...  
206 
211 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

207 
212 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

208 
213 
\return negative log likelihood


214 
\ingroup STATLIB

209 
215 
**/

210 
216 
dvariable dzinbinom(const dvector& x, const dvar_vector& mu, const dvar_vector& k, const prevariable& p)

211 
217 
{

...  ...  
250 
256 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

251 
257 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

252 
258 
\return negative log likelihood


259 
\ingroup STATLIB

253 
260 
**/

254 
261 
df1b2variable dzinbinom(const dvector& x, const df1b2vector& mu, const df1b2variable& k, const df1b2vector& p)

255 
262 
{

...  ...  
290 
297 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

291 
298 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

292 
299 
\return negative log likelihood


300 
\ingroup STATLIB

293 
301 
**/

294 
302 
df1b2variable dzinbinom(const dvector& x, const df1b2vector& mu, const df1b2vector& k, const df1b2vector& p)

295 
303 
{

...  ...  
331 
339 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

332 
340 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

333 
341 
\return negative log likelihood


342 
\ingroup STATLIB

334 
343 
**/

335 
344 
dvariable dzinbinom(const dvector& x, const dvar_vector& mu, const prevariable& k, const dvar_vector& p)

336 
345 
{

...  ...  
371 
380 
\param k is the overdispersion parameter, i.e. size, i.e. shape parameter of underlying heterogeneity (different from tau). should be >0

372 
381 
\param p is the zero inflation paramerer, i.e. extra chance of observing zeros. 0<p<1.

373 
382 
\return negative log likelihood


383 
\ingroup STATLIB

374 
384 
**/

375 
385 
dvariable dzinbinom(const dvector& x, const dvar_vector& mu, const dvar_vector& k, const dvar_vector& p)

376 
386 
{
