```{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,
* 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.
* $p$: estimated proportions,
* $\beta$: estimated regression matrix,
* $b$: estimated bias.
* $p$: estimated proportions,
* $\beta$: estimated regression matrix,
* $b$: estimated bias.
# 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")
```
# 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