refundr/README.Rmd at dev · tidyfun/refundr · GitHub

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---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "##",
  fig.width = 8,
  fig.height = 5.5,
  out.width = "90%"
)


library(tidyverse)
library(tidyfun)
library(refundr)
library(viridisLite)

theme_set(theme_minimal() + theme(legend.position = "bottom"))

options(
  ggplot2.continuous.colour = "viridis",
  ggplot2.continuous.fill = "viridis"
)
scale_colour_discrete = scale_colour_viridis_d
scale_fill_discrete = scale_fill_viridis_d

library("refundr")

```

# refundr

<!-- badges: start -->
[![Travis build status](https://travis-ci.org/tidyfun/refundr.svg?branch=master)](https://travis-ci.org/tidyfun/refundr)
[![AppVeyor build status](https://ci.appveyor.com/api/projects/status/github/tidyfun/refundr?branch=master&svg=true)](https://ci.appveyor.com/project/tidyfun/refundr)
<!-- badges: end -->

The goal of **`refundr`** is to interface **`refund`** and **`tidyfun`**.

## Installation

``` r
devtools::install_github("tidyfun/refundr")
```

## `rfr_fpca()`

The `rfr_fpca()` function peforms `fpca` using functions from the `refund` package. The input is a `tfd` column.

Below are examples using the dti and chf datasets.


```{r}

library(refundr)
library(tidyfun)
library(tidyverse)

# irregular data
data(dti_df)
dti_fpca = rfr_fpca(Y = "cca", data = dti_df)

dti_df %>%
  modelr::add_predictions(dti_fpca, var = "cca_fits") %>%
  filter(case == "control") %>%
  ggplot(aes(y = cca_fits)) +
  geom_spaghetti(alpha = .4) +
  geom_spaghetti(aes(y = cca), color = "blue", alpha = .3) +
  facet_grid(~sex)

# regular data
data(chf_df)
dti_fpca = rfr_fpca(Y = "activity", data = chf_df)
```