Fix current vignette

[morpheus.git] / vignettes / report.Rmd

diff --git a/vignettes/report.Rmd b/vignettes/report.Rmd
index 84dc5b6..de98b9f 100644 (file)
--- a/vignettes/report.Rmd
+++ b/vignettes/report.Rmd
@@ -7,6 +7,9 @@ output:
     toc_depth: 1
 ---
 
     toc_depth: 1
 ---
 

+\renewcommand{\P}{\mathrm{P}}
+\newcommand{\R}{\mathbb{R}}
+

 ```{r setup,  results="hide", include=FALSE}
 knitr::opts_chunk$set(echo = TRUE, include = TRUE,
   cache = TRUE, comment="", cache.lazy = FALSE,
 ```{r setup,  results="hide", include=FALSE}
 knitr::opts_chunk$set(echo = TRUE, include = TRUE,
   cache = TRUE, comment="", cache.lazy = FALSE,


@@ -56,7 +59,7 @@ The model of population mixture of binary regressions is given by:
 
 \begin{equation}
 \label{mixturemodel1}
 
 \begin{equation}
 \label{mixturemodel1}

-\PP_{\theta}(Y=1\vert X=x)=\sum^{K}_{k=1}\omega_k g(<\beta_k,x>+b_k).
+\P_{\theta}(Y=1\vert X=x)=\sum^{K}_{k=1}\omega_k g(<\beta_k,x>+b_k).

 \end{equation}
 
 ## Algorithm, theoretical garantees
 \end{equation}
 
 ## Algorithm, theoretical garantees


@@ -110,10 +113,12 @@ mu <- computeMu(io$X, io$Y, optargs=list(K=2))
 ```
 
 The optional argument, "optargs", is a list which can provide
 ```
 
 The optional argument, "optargs", is a list which can provide

+

  * the number of clusters $K$,
  * the moments matrix $M$ (computed with the "computeMoments()" function),
  * the joint-diagonalisation method ("uwedge" or "jedi"),
  * the number of random vectors for joint-diagonalization.
  * the number of clusters $K$,
  * the moments matrix $M$ (computed with the "computeMoments()" function),
  * the joint-diagonalisation method ("uwedge" or "jedi"),
  * the number of random vectors for joint-diagonalization.

+

 See ?computeMu and the code for more details.
 
 ### Estimation of the other parameters
 See ?computeMu and the code for more details.
 
 ### Estimation of the other parameters


@@ -131,6 +136,7 @@ theta <- algopt$run(x0)
 ```
 
 Now theta is a list with three slots:
 ```
 
 Now theta is a list with three slots:

+

  * $p$: estimated proportions,
  * $\beta$: estimated regression matrix,
  * $b$: estimated bias.
  * $p$: estimated proportions,
  * $\beta$: estimated regression matrix,
  * $b$: estimated bias.


@@ -186,7 +192,7 @@ Several plots are available: histograms, boxplots, or curves of coefficients.
 We illustrate boxplots and curves here (histograms function uses the same arguments,
 see ?plotHist).
 
 We illustrate boxplots and curves here (histograms function uses the same arguments,
 see ?plotHist).
 

-```
+```{r, results="show", include=TRUE, echo=TRUE}

 # Second row, first column; morpheus on the left, flexmix on the right
 plotBox(mr1, 2, 1, "Target value: -1")
 ```
 # Second row, first column; morpheus on the left, flexmix on the right
 plotBox(mr1, 2, 1, "Target value: -1")
 ```


@@ -224,7 +230,7 @@ for (i in 1:2)
   mr2[[i]] <- alignMatrices(mr2[[i]], ref=beta, ls_mode="exact")
 ```
 
   mr2[[i]] <- alignMatrices(mr2[[i]], ref=beta, ls_mode="exact")
 ```
 

-```
+```{r, results="show", include=TRUE, echo=TRUE}

 # Second argument = true parameters matrix; third arg = index of method (here "morpheus")
 plotCoefs(mr2, beta, 1)
 # Real params are on the continous line; estimations = dotted line
 # Second argument = true parameters matrix; third arg = index of method (here "morpheus")
 plotCoefs(mr2, beta, 1)
 # Real params are on the continous line; estimations = dotted line