| 
    MuGen
    
   Multitrait genetics 
   | 
 
Individual vector of means with blocks of traits. More...
#include <MuGen.h>
Public Member Functions | |
| MVnormMuBlk () | |
| Default constructor.  | |
| MVnormMuBlk (gsl_matrix *mn, const size_t &iRw, const vector< size_t > &blkStart, const size_t &up) | |
| Deterministic constructor.  More... | |
| MVnormMuBlk (gsl_matrix *mn, const size_t &iRw, const gsl_vector *sd, const gsl_rng *r, const vector< size_t > &blkStart, const vector< vector< size_t > > &eachLL, const size_t &up) | |
| Univariate stochastic constructor.  More... | |
| virtual | ~MVnormMuBlk () | 
| Destructor.  | |
| const size_t * | up () const | 
| Points to the prior.  More... | |
| void | update (const Grp &dat, const SigmaI &SigIm, const gsl_rng *r) | 
| Gaussian likelihood.  More... | |
| void | update (const Grp &dat, const Qgrp &q, const SigmaI &SigIm, const gsl_rng *r) | 
| Sudent- \(t\) likelihood.  More... | |
| void | update (const Grp &dat, const SigmaI &SigIm, const SigmaI &SigIp, const gsl_rng *r) | 
| Gaussian likelihood, Gaussian prior.  More... | |
| void | update (const Grp &dat, const SigmaI &SigIm, const double &qPr, const SigmaI &SigIp, const gsl_rng *r) | 
| Gaussian likelihood, Student- \(t\) prior.  More... | |
| void | update (const Grp &dat, const Qgrp &q, const SigmaI &SigIm, const SigmaI &SigIp, const gsl_rng *r) | 
| Student- \(t\) likelihood, Gaussian prior.  More... | |
| void | update (const Grp &dat, const Qgrp &q, const SigmaI &SigIm, const double &qPr, const SigmaI &SigIp, const gsl_rng *r) | 
| Student- \(t\) likelihood, Student- \(t\) prior.  More... | |
| void | update (const Grp &dat, const SigmaI &SigIm, const Grp &muPr, const SigmaI &SigIp, const gsl_rng *r) | 
| Gaussian likelihood, Gaussian prior.  More... | |
| void | update (const Grp &dat, const SigmaI &SigIm, const Grp &muPr, const double &qPr, const SigmaI &SigIp, const gsl_rng *r) | 
| Gaussian likelihood, Student- \(t\) prior.  More... | |
| void | update (const Grp &dat, const Qgrp &q, const SigmaI &SigIm, const Grp &muPr, const SigmaI &SigIp, const gsl_rng *r) | 
| Student- \(t\) likelihood, Gaussian prior.  More... | |
| void | update (const Grp &dat, const Qgrp &q, const SigmaI &SigIm, const Grp &muPr, const double &qPr, const SigmaI &SigIp, const gsl_rng *r) | 
| Student- \(t\) likelihood, Student- \(t\) prior.  More... | |
  Public Member Functions inherited from MVnorm | |
| MVnorm (const MVnorm &) | |
| Copy constructor.  More... | |
| MVnorm & | operator= (const MVnorm &) | 
| Assignement operator.  More... | |
| virtual | ~MVnorm () | 
| Virtual destructor.  More... | |
| virtual double | mhl (const MVnorm *x, const SigmaI &SigI) | 
| Mahalanobis distance to a vector.  More... | |
| virtual double | mhl (const MVnorm *x, const SigmaI &SigI) const | 
| Mahalanobis distance to a vector.  More... | |
| virtual double | mhl (const gsl_vector *x, const SigmaI &SigI) | 
| Mahalanobis distance to a vector.  More... | |
| virtual double | mhl (const gsl_vector *x, const SigmaI &SigI) const | 
| Mahalanobis distance to a vector.  More... | |
| virtual double | mhl (const SigmaI &SigI) | 
| Mahalanobis distance to zero.  More... | |
| virtual double | mhl (const SigmaI &SigI) const | 
| Mahalanobis distance to zero.  More... | |
| double | density (const gsl_vector *theta, const SigmaI &SigI) | 
| Multivariate Gaussian density.  More... | |
| double | density (const gsl_vector *theta, const SigmaI &SigI) const | 
| Multivariate Gaussian density.  More... | |
| double | density (const MVnorm *theta, const SigmaI &SigI) | 
| Multivariate Gaussian density.  More... | |
| double | density (const MVnorm *theta, const SigmaI &SigI) const | 
| Multivariate Gaussian density.  More... | |
| void | save (const string &fileNam, const char *how="a") | 
| Save function.  More... | |
| void | save (FILE *fileStr) | 
| Save function.  More... | |
| double | operator[] (const size_t i) const | 
| Subscript operator.  More... | |
| void | valSet (const size_t i, const double x) | 
| Setting an element to a value.  More... | |
| const gsl_vector * | getVec () const | 
| Access the location vector.  More... | |
| size_t | len () const | 
| Length of the location vector.  More... | |
| virtual size_t | nMissP () const | 
| Number of missing values.  More... | |
| virtual const vector< size_t > | getMisPhen () const | 
| Indexes of missing values.  More... | |
| virtual const vector< size_t > * | down () const | 
| Points to the corresponding data.  More... | |
| virtual double | scalePar () const | 
| Scale parameter.  More... | |
Protected Attributes | |
| const size_t * | _upLevel | 
| Pointer to a row index of the prior.  More... | |
| const vector< size_t > * | _blkStart | 
| Start positions of blocks.  More... | |
| vector< gsl_vector_view > | _eachVec | 
| Trait blocks.  More... | |
| const vector< vector< size_t > > * | _eachLL | 
| Data matrix row indexes.  More... | |
  Protected Attributes inherited from MVnorm | |
| gsl_vector_view | _vec | 
| Data vector.  More... | |
| size_t | _d | 
| Length of the data vector.  | |
Additional Inherited Members | |
  Protected Member Functions inherited from MVnorm | |
| MVnorm () | |
| Default constructor.  More... | |
| MVnorm (const size_t &d) | |
| Dimension-only constructor.  More... | |
| MVnorm (gsl_vector *mn) | |
| Dimension and vector value constructor.  More... | |
| MVnorm (gsl_vector *mn, const gsl_vector *sd, const gsl_rng *r) | |
| Univariate Gaussian constructor.  More... | |
| MVnorm (gsl_vector *mn, const gsl_matrix *Sig, const gsl_rng *r) | |
| Multivariate Gaussian constructor.  More... | |
| MVnorm (gsl_matrix *mn, const size_t &iRw) | |
| Dimension and vector value constructor.  More... | |
| MVnorm (gsl_matrix *mn, const size_t &iRw, const gsl_vector *sd, const gsl_rng *r) | |
| Univariate Gaussian constructor with a matrix.  More... | |
| MVnorm (gsl_matrix *mn, const size_t &iRw, const gsl_matrix *Sig, const gsl_rng *r) | |
| Multivariate Gaussian constructor with a matrix.  More... | |
Individual vector of means with blocks of traits.
Implements separate models for blocks of traits. The likelihood covariance matrix is block-diagonal. Traits of the same block have to be contiguous within the vector.
| MVnormMuBlk::MVnormMuBlk | ( | gsl_matrix * | mn, | 
| const size_t & | iRw, | ||
| const vector< size_t > & | blkStart, | ||
| const size_t & | up | ||
| ) | 
Deterministic constructor.
Sets up the member variables to point to blocks of traits in the matrix mn, but does not perform stochastic intitialization.
| [in] | gsl_matrix* | mean values matrix | 
| [in] | size_t& | row index of the mean values matrix | 
| [in] | vector<size_t>& | vector of start indexes for each block | 
| [in] | size_t& | row index of the prior matrix | 
| MVnormMuBlk::MVnormMuBlk | ( | gsl_matrix * | mn, | 
| const size_t & | iRw, | ||
| const gsl_vector * | sd, | ||
| const gsl_rng * | r, | ||
| const vector< size_t > & | blkStart, | ||
| const vector< vector< size_t > > & | eachLL, | ||
| const size_t & | up | ||
| ) | 
Univariate stochastic constructor.
Sets initial values independently for each trait, modifying the matrix row that corresponds to this vector.
| [in] | gsl_matrix* | mean values matrix | 
| [in] | size_t& | row index of the mean values matrix | 
| [in] | gsl_vector* | vector of standard deviations | 
| [in] | gsl_rng* | pointer to a PNG | 
| [in] | vector<size_t>& | vector of start indexes for each block | 
| [in] | vector< | vector<size_t> >& vector of lower-level index vectors | 
| [in] | size_t& | row index of the prior matrix | 
      
  | 
  inlinevirtual | 
Points to the prior.
Access to the pointer to the correspoding vector of priors. Is non-zero only for classes where a prior is implemented.
Reimplemented from MVnorm.
      
  | 
  virtual | 
Student- \(t\) likelihood, Student- \(t\) prior.
| [in] | Grp& | data for the likelihood | 
| [in] | Qgrp& | vector Student- \(t\) covariance scale parameter for the likelihood covariance | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | double& | Student- \(t\) scale parameter for the prior covariance | 
| [in] | SigmaI& | prior inverse-covariance matrix | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
      
  | 
  virtual | 
Student- \(t\) likelihood, Student- \(t\) prior.
| [in] | Grp& | data for the likelihood | 
| [in] | Qgrp& | vector Student- \(t\) covariance scale parameter for the likelihood covariance | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | Grp& | prior mean | 
| [in] | double& | Student- \(t\) scale parameter for the prior covariance | 
| [in] | SigmaI& | prior inverse-covariance matrix | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
      
  | 
  virtual | 
Student- \(t\) likelihood, Gaussian prior.
| [in] | Grp& | data for the likelihood | 
| [in] | Qgrp& | vector Student- \(t\) covariance scale parameter for the likelihood covariance | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | Grp& | prior mean | 
| [in] | SigmaI& | prior inverse-covariance matrix | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
Sudent- \(t\) likelihood.
| [in] | Grp& | data | 
| [in] | Qgrp& | vector of Student- \(t\) covariance scale parameters for the likelihood covariance | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
      
  | 
  virtual | 
Student- \(t\) likelihood, Gaussian prior.
| [in] | Grp& | data for the likelihood | 
| [in] | Qgrp& | vector of Student- \(t\) covariance scale parameters for the likelihood covariance | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | SigmaI& | prior inverse-covariance matrix | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
      
  | 
  virtual | 
Gaussian likelihood, Student- \(t\) prior.
| [in] | Grp& | data for the likelihood | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | double& | Student- \(t\) scale parameter for the prior covariance | 
| [in] | SigmaI& | prior inverse-covariance matrix | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
      
  | 
  virtual | 
Gaussian likelihood, Student- \(t\) prior.
| [in] | Grp& | data for the likelihood | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | Grp& | prior mean | 
| [in] | double& | Student- \(t\) scale parameter for the prior covariance | 
| [in] | SigmaI& | prior inverse-covariance matrix | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
      
  | 
  virtual | 
Gaussian likelihood, Gaussian prior.
| [in] | Grp& | data for the likelihood | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | Grp& | prior mean | 
| [in] | SigmaI& | prior inverse-covariance matrix | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
Gaussian likelihood.
| [in] | Grp& | data | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
      
  | 
  virtual | 
Gaussian likelihood, Gaussian prior.
| [in] | Grp& | data for the likelihood | 
| [in] | SigmaI& | inverse-covariance matrix for the likelihood | 
| [in] | SigmaI& | prior inverse-covariance matrix | 
| [in] | gsl_rng* | pointer to a PNG | 
Implements MVnorm.
      
  | 
  protected | 
Start positions of blocks.
Pointer to the vector that's in the corresponding Grp class.
      
  | 
  protected | 
Data matrix row indexes.
Each block of traits can have a different number and identity of rows in the data matrix it refers to. Each vector of size_t in this vector corresponds to a block, so the size of this should be the same as the size of *_eachVec*. This member is a pointer to the vector that's in the corresponding Grp class.
      
  | 
  protected | 
Trait blocks.
Vector views of vector pieces, each corresponding to a block of variables. Pointer to the vector that's in the corresponding Grp class.
      
  | 
  protected | 
Pointer to a row index of the prior.
This has to be the same for all the blocks.