Revision 593 trunk/contrib/statslib/dzinbinom.cpp

dzinbinom.cpp (revision 593)
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 92
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
{

Also available in: Unified diff