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Functions
Description
Multivariate Normal distribution which uses the covariance matrix as input. It should be used with its companion object NcmModelMVND.
Functions
ncm_data_gauss_cov_mvnd_new ()
NcmDataGaussCovMVND *
ncm_data_gauss_cov_mvnd_new (const guint dim);
Creates a new dim
-dimensional MVND.
ncm_data_gauss_cov_mvnd_new_full ()
NcmDataGaussCovMVND * ncm_data_gauss_cov_mvnd_new_full (const guint dim,const gdouble sigma_min,const gdouble sigma_max,const gdouble cor_level,const gdouble mean_min,const gdouble mean_max,NcmRNG *rng);
Creates a new dim
-dimensional MVND and generate using rng
a mean
and correlation matrix using the parameters above.
Parameters
dim |
dimension of the MVND |
|
sigma_min |
minimum value of $\sigma_i$ |
|
sigma_max |
maximum value of $\sigma_i$ |
|
cor_level |
correlation level |
|
mean_min |
minimum mean $\mu_i$ |
|
mean_max |
maximum mean $\mu_i$ |
|
rng |
a NcmRNG |
ncm_data_gauss_cov_mvnd_ref ()
NcmDataGaussCovMVND *
ncm_data_gauss_cov_mvnd_ref (NcmDataGaussCovMVND *data_mvnd);
Increases the reference count of data_mvnd
by one.
ncm_data_gauss_cov_mvnd_free ()
void
ncm_data_gauss_cov_mvnd_free (NcmDataGaussCovMVND *data_mvnd);
Decreases the reference count of data_mvnd
by one.
ncm_data_gauss_cov_mvnd_clear ()
void
ncm_data_gauss_cov_mvnd_clear (NcmDataGaussCovMVND **data_mvnd);
If data_mvnd
is different from NULL, decreases the reference count of
data_mvnd
by one and sets data_mvnd
to NULL.
ncm_data_gauss_cov_mvnd_gen_cov_mean ()
void ncm_data_gauss_cov_mvnd_gen_cov_mean (NcmDataGaussCovMVND *data_mvnd,const gdouble sigma_min,const gdouble sigma_max,const gdouble cor_level,const gdouble mean_min,const gdouble mean_max,NcmRNG *rng);
Generates using rng
the mean and correlation matrix using
the parameters above.
Parameters
data_mvnd |
||
sigma_min |
minimum value of $\sigma_i$ |
|
sigma_max |
maximum value of $\sigma_i$ |
|
cor_level |
correlation level |
|
mean_min |
minimum mean $\mu_i$ |
|
mean_max |
maximum mean $\mu_i$ |
|
rng |
a NcmRNG |
ncm_data_gauss_cov_mvnd_set_cov_mean ()
void ncm_data_gauss_cov_mvnd_set_cov_mean (NcmDataGaussCovMVND *data_mvnd,NcmVector *mean,NcmMatrix *cov);
Sets the mean and covariance of data_mvnd
.
ncm_data_gauss_cov_mvnd_peek_mean ()
NcmVector *
ncm_data_gauss_cov_mvnd_peek_mean (NcmDataGaussCovMVND *data_mvnd);
Peeks current mean vector.
ncm_data_gauss_cov_mvnd_gen ()
NcmVector * ncm_data_gauss_cov_mvnd_gen (NcmDataGaussCovMVND *data_mvnd,NcmMSet *mset,gpointer obj,NcmDataGaussCovMVNDBound bound,NcmRNG *rng,gulong *N);
Generates one realization of the MVND. If bound
is not NULL,
generates realizations untill bound
returns TRUE.
ncm_data_gauss_cov_mvnd_est_ratio ()
gdouble ncm_data_gauss_cov_mvnd_est_ratio (NcmDataGaussCovMVND *data_mvnd,NcmMSet *mset,gpointer obj,NcmDataGaussCovMVNDBound bound,gulong *N,gulong *Nin,const gdouble reltol,NcmRNG *rng);
Estimate the ratio between accepted realizations and total number
of realizations. The variable reltol
controls the relative tolerance
on the ratio estimate. The variables N
and Nin
can be used to inform
previous number of realizations.
ncm_data_gauss_cov_mvnd_log_info ()
void
ncm_data_gauss_cov_mvnd_log_info (NcmDataGaussCovMVND *data_mvnd);
Logs mean and covariance matrix.