---
title: "Help for old friends"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Help for old friends}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---


```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup, include=FALSE}
library("brokenstick")
```

# Background

The `brokenstick` package has three major interfaces:

1. Up to version `brokenstick 0.62.1` (before May 2020) 
2. Up to version `brokenstick 1.1.1` (May 2020 - Nov 2021) 
3. Versions higher than `brokenstick 2.0.0` (Nov 2021 - now)

This document summarises the main changes in `brokenstick 2.0.0`. See "Help for old friends" in `brokenstick 1.1.1` for an overview of the previous changes from `0.75.0` to `1.1.1`.

## Main changes

1. Function `brokenstick()` in version `2.0.0` sets the Kasim-Raudenbush sampler as the default method. The former method `lme4::lmer()` remains available by setting `method = "lmer"` argument. 

2. Version `2.0.0` adopts the variable names of the `coda` package (e.g., `start`, `end`, `thin`, `niter`, and so on) and stores the results of the Kasim-Raudenbush sampler as objects of class `mcmc`. 

3. For `method = "kr"` one may now inspect the solution of the sampler by standard functions from the `coda` package. For `method = "lmer"` we can apply functions from the `lme4` package for `merMod` objects. 

4. Version `2.0.0` redefines the `brokenstick` class. New entries include `call`, `formula`, `internal`, `sample`, `light`, `data`, `imp` and `mod`. Removed entries are `knots` (renamed to `internal`) and `draws` (renamed to `imp`). We may omit the `newdata` argument for the training data. Setting `light = TRUE` creates a small version of the `brokenstick` object. Objects of class `brokenstick` are not backwards compatible, so one should regenerate objects of class `brokenstick` in order use newer features in `2.0.0`.

5. Version `2.0.0` conforms to classic model fitting interface in `R`. Renames the `new_data` argument to `newdata` to conform to `predict.lm()`. Methods `plot()` and `predict()` no longer require a `newdata` argument. All special cases of `predict()` updated and explained in documentation and examples.

6. Version `2.0.0` adds methods `coef()`, `fitted()`, `model.frame()`, `model.matrix()`, `print()` and `summary()` for the `brokenstick` object.

7. Simplifies algorithmic control. Renames `control_brokenstick()` to `set_control()` and removes a layer in the control list.

## Minor changes

- Stabilises the `rgamma()` calls in KR-algorithm for edge cases.
- `predict_brokenstick()` can now work with the both (internal) training and (external) test data. 
- Removes the superfluous `type` argument from `predict.brokenstick()`
- Adds a function `get_omega()` to extract the variance-covariance matrix of the broken stick estimates
- Adds choice `"dropfirst"` to `get_knots()`
- Improves error messages of edge cases in `test-brokenstick_edge.R`
- Perform stricter tests on arguments of `brokenstick()`
- Introduces argument `warn_splines` in `make_basis()` to suppress uninteresting warns from `splines::bs()`
- Removes superfluous `knotnames` argument in `make_basis()`
- Argument `x` in `make_basis()` is now a vector instead of a column vector
- Introduces new `xname` argument in `make_basis()` to set the xname


# Install legacy version

We recommend changing your code to reflect the above changes. If needed, version `1.1.1` can be installed as

```{r eval=FALSE}
library("devtools")
install_github("growthcharts/brokenstick@9b969af")
```

# Examples

## Example 1: Fit model

Fit model, version `0.75.0` - `1.1.1`:

```{r fit-v1, eval = FALSE}
data <- brokenstick::smocc_200

# formula interface
fit1 <- brokenstick(hgt_z ~ age | id, data)

# XY interface - numeric vector
# Deprecated in v2.0.0
fit2 <- with(data, brokenstick(age, hgt_z, id))

# XY interface - data.frame
# Deprecated in v2.0.0
fit3 <- with(data, brokenstick(data.frame(age), hgt_z, id))

# XY interface - matrix
# Deprecated in v2.0.0
tt <- as.matrix(data[, c(1, 2, 7)])
fit4 <- brokenstick(tt[, "age", drop = FALSE],
                    tt[, "hgt_z", drop = FALSE],
                    tt[, "id", drop = FALSE])
```

Fit model, version `2.0.0`:


```{r fit-v2}
data <- brokenstick::smocc_200

# formula interface
fit1 <- brokenstick(hgt_z ~ age | id, data)
```


## Example 2: Predict model

Predict model, version `0.75.0` - `1.1.1`:

```{r predict-v1}
# predict at observed data
p1 <- predict(fit1, data)

# predict at knots
p2 <- predict(fit1, data, x = "knots")

# predict at both observed data and knots
p3 <- predict(fit1, data, x = "knots", strip_data = FALSE)

# predict knots, broad matrix
p4 <- predict(fit1, data, x = "knots", shape = "wide")
```

Predict model, version `2.0.0`:

```{r predict-v2}
# predict at observed data
p1 <- predict(fit1)

# predict at knots
p2 <- predict(fit1, x = "knots")

# predict at both observed data and knots
p3 <- predict(fit1, x = "knots", strip_data = FALSE)

# predict knots, broad matrix
p4 <- predict(fit1, x = "knots", shape = "wide")
```

## Example 3: Plot model

Plot trajectories, version `0.75.0` - `1.1.1`:

```{r plot-v1, fig.height=3, fig.width=7}
ids <- c(10001, 10005, 10022)
plot(fit1, data, group = ids, what = "all")
```

Plot trajectories, version `2.0.0`:

```{r plot-v2, fig.height=3, fig.width=7}
ids <- c(10001, 10005, 10022)
plot(fit1, group = ids, what = "all")
```
