R: Sliding window calculation over multiple inputs...

slide2 {tsibble} | R Documentation

## Sliding window calculation over multiple inputs simultaneously

### Description

Rolling window with overlapping observations:

- `slide2()` and `pslide()` always returns a list.

- `slide2_lgl()`, `slide2_int()`, `slide2_dbl()`, `slide2_chr()` use the same arguments as `slide2()`, but return vectors of the corresponding type.

- `slide2_dfr()` `slide2_dfc()` return data frames using row-binding & column-binding.

### Usage

    slide2(.x, .y, .f, ..., .size = 1, .fill = NA, .partial = FALSE,
      .align = "right", .bind = FALSE)

    slide2_dfr(.x, .y, .f, ..., .size = 1, .fill = NA, .partial = FALSE,
      .align = "right", .bind = FALSE, .id = NULL)

    slide2_dfc(.x, .y, .f, ..., .size = 1, .fill = NA, .partial = FALSE,
      .align = "right", .bind = FALSE)

    pslide(.l, .f, ..., .size = 1, .fill = NA, .partial = FALSE,
      .align = "right", .bind = FALSE)

    pslide_dfr(.l, .f, ..., .size = 1, .fill = NA, .partial = FALSE,
      .align = "right", .bind = FALSE, .id = NULL)

    pslide_dfc(.l, .f, ..., .size = 1, .fill = NA, .partial = FALSE,
      .align = "right", .bind = FALSE)

### Arguments

`.x, .y` | Objects to slide over simultaneously.
`.f` | A function, formula, or atomic vector. If a function, it is used as is. If a formula, e.g. `~ .x + 2`, it is converted to a function. There are three ways to refer to the arguments: For a single argument function, use `.` For a two argument function, use `.x` and `.y` For more arguments, use `..1`, `..2`, `..3` etc This syntax allows you to create very compact anonymous functions. If character vector, numeric vector, or list, it is converted to an extractor function. Character vectors index by name and numeric vectors index by position; use a list to index by position and name at different levels. Within a list, wrap strings in `get-attr()` to extract named attributes. If a component is not present, the value of `.default` will be returned.
`...` | Additional arguments passed on to `.f`.
`.size` | An integer for window size. If positive, moving forward from left to right; if negative, moving backward (from right to left).
`.fill` | A value to fill at the left of the data range (`NA` by default). `NULL` means no filling.
`.partial` | if `TRUE`, partial sliding.
`.align` | Align index at the "right", "centre"/"center", or "left" of the window. If `.size` is even for center alignment, "centre-right" & "centre-left" is needed.
`.bind` | If `.x` is a list, should `.x` be combined before applying `.f`? If `.x` is a list of data frames, row binding is carried out.
`.id` | If not `NULL` a variable with this name will be created giving either the name or the index of the data frame.
`.l` | A list of lists. The length of `.l` determines the number of arguments that `.f` will be called with. List names will be used if present.

### See Also

- tile2 for tiling window without overlapping observations

- stretch2 for expanding more observations

Other sliding window functions: `slide`

### Examples

    x <- 1:5
    y <- 6:10
    z <- 11:15
    lst <- list(x = x, y = y, z = z)
    df <- as.data.frame(lst)
    slide2(x, y, sum, .size = 2)
    slide2(lst, lst, ~ ., .size = 2)
    slide2(df, df, ~ ., .size = 2)
    pslide(lst, ~ ., .size = 1)
    pslide(list(lst, lst), ~ ., .size = 2)

    ###
    # row-wise sliding over data frame
    ###

    my_df <- data.frame(
      group = rep(letters[1:2], each = 8),
      x = c(1:8, 8:1),
      y = 2 * c(1:8, 8:1) + rnorm(16),
      date = rep(as.Date("2016-06-01") + 0:7, 2)
    )

    slope <- function(...) {
      data <- list(...)
      fm <- lm(y ~ x, data = data)
      coef(fm)[[2]]
    }

    my_df %>%
      nest(-group) %>%
      mutate(slope = purrr::map(data, ~ pslide_dbl(., slope, .size = 2))) %>%
      unnest()
    ## window over 2 months
    pedestrian %>%
      filter(Sensor == "Southern Cross Station") %>%
      index_by(yrmth = yearmonth(Date_Time)) %>%
      nest(-yrmth) %>%
      mutate(ma = slide_dbl(data, ~ mean(.$Count), .size = 2, .bind = TRUE))
    # row-oriented workflow
    ## Not run:
    my_diag <- function(...) {
      data <- list(...)
      fit <- lm(Count ~ Time, data = data)
      tibble(fitted = fitted(fit), resid = residuals(fit))
    }
    pedestrian %>%
      filter_index("2015-01") %>%
      nest(-Sensor) %>%
      mutate(diag = purrr::map(data, ~ pslide_dfr(., my_diag, .size = 48)))

    ## End(Not run)

[Package tsibble version 0.6.2 Index]