Changeset 693 for library/doc/tutorial

Timestamp:

11/02/09 17:27:29 (15 years ago)

Author:

mido

Message:

mpdf renamed to pdf in the whole library

Location:

library/doc/tutorial

Files:

• 01userguide.dox (modified) (5 diffs)
• 02userguide2.dox (modified) (1 diff)
• unit_testing.dox (modified) (1 diff)

library/doc/tutorial/01userguide.dox

@@ -162 +162 @@
      - bdm::CsvFileDS
      - bdm::ITppFileDS
- - bdm::MpdfDS
+ - bdm::PdfDS
  - bdm::stateDS
 
@@ -243 +243 @@
 fu.R     = 0.2;
 
-DS.class = 'MpdfDS';
-DS.mpdf.class  = 'mprod';
-DS.mpdf.mpdfs  = {fy, epdf2mpdf(fu)};
+DS.class = 'pdfDS';
+DS.pdf.class  = 'mprod';
+DS.pdf.pdfs  = {fy, epdf2mpdf(fu)};
 \endcode
 
@@ -252 +252 @@
  - naming convention 'mlnorm\<ldmat\>' relates to the concept of templates in C++. For those unfamiliar with this concept, it is basicaly a way how to share code for different flavours of the same object. Note that mlnorm exist in three versions: mlnorm\<ldmat\>, mlnorm<chmat>, mlnorm<fsqmat>. Those classes act identically the only difference is that the internal data are stored either in LD decomposition, choleski decomposition or full matrices, respectively. 
  - the same concept is used for enorm, where enorm<chmat> and enorm<fsqmat> are also possible. In this particular use, these objects are equivalent. In specific situation, e.g. Kalman filter implemented on Choleski decomposition (bdm::KalmanCh), only enorm<chmat> is approprate.
- - class 'mprod' represents the chain rule of probability. Attribute \c mpdfs of its configuration structure is a list of conditional densities. Conditional density \f$ f(a|b)\f$ is represented by class \c mpdf and its offsprings. Class \c RV is used to describe both variables before conditioning (field \c rv ) and after conditioning sign (field \c rvc).
- - due to simplicity of implementation, mprod accept only conditional densities in the field \c mpdfs. Hence, the pdf \f$ f(u_t)\f$ must be converted to conditional density with empty conditioning, \f$ f(u_t| \{\})\f$. This is achieved by calling function epdf2mpdf which is only a trivial wrapper creating class bdm::mepdf.
+ - class 'mprod' represents the chain rule of probability. Attribute \c pdfs of its configuration structure is a list of conditional densities. Conditional density \f$ f(a|b)\f$ is represented by class \c pdf and its offsprings. Class \c RV is used to describe both variables before conditioning (field \c rv ) and after conditioning sign (field \c rvc).
+ - due to simplicity of implementation, mprod accept only conditional densities in the field \c pdfs. Hence, the pdf \f$ f(u_t)\f$ must be converted to conditional density with empty conditioning, \f$ f(u_t| \{\})\f$. This is achieved by calling function epdf2mpdf which is only a trivial wrapper creating class bdm::mepdf.
  
  
@@ -260 +260 @@
 \subsection ug_ini Initializing simulation
 
-When zeros are not appropriate initial conditions, the correct conditions can be set using additional commands (see bdm::MpdfDS.from_setting() ):
+When zeros are not appropriate initial conditions, the correct conditions can be set using additional commands (see bdm::pdfDS.from_setting() ):
 \code
 DS.init_rv = RV({'y','y','y'}, [1,1,1], [-1,-2,-3]);
@@ -281 +281 @@
 Data=[M.y; M.u];
 drv = RVjoin({y,u});
-save mpdfds_results Data drv
+save pdfds_results Data drv
 \endcode
 Such data can be later provided e.g. by MemDS

library/doc/tutorial/02userguide2.dox

@@ -106 +106 @@
 \section ug2_bm_composition Composition of estimators
 
-Similarly to mpdfs which could be composed via \c mprod, the Bayesian models can be composed. However, justification of this step is less clear than in the case of epdfs.
+Similarly to pdfs which could be composed via \c mprod, the Bayesian models can be composed. However, justification of this step is less clear than in the case of epdfs.
 
 One possible theoretical base of composition is the Marginalized particle filter, which splits the prior and the posterior in two parts:

library/doc/tutorial/unit_testing.dox

@@ -118 +118 @@
 
 Testsuite has explicit support for testing classes derived from
-bdm::epdf and bdm::mpdf: bdm::epdf_harness and
-bdm::mpdf_harness. These classes run a list of tests on objects
+bdm::epdf and bdm::pdf: bdm::epdf_harness and
+bdm::pdf_harness. These classes run a list of tests on objects
 created from the specified configuration file (normally called
 <classname>.cfg) and check them against expected values also