# slope: slope In rtrend: Trend Estimating Tools

 slope_sen R Documentation

## slope

### Description

• `slope` : linear regression slope

• `slope_p` : linear regression slope and p-value

• `slope_mk` : mann kendall Sen's slope and p-value

• `slope_sen` : same as `slope_mk`, but with no p-value

• `slope_boot`: bootstrap slope and p-value

### Usage

``````slope_sen(y, x = NULL)

slope(y, x, ...)

slope_p(y, x, fast = TRUE)

slope_sen_r(y, x = seq_along(y), ...)

slope_mk(y, x = NULL, ...)

slope_boot(y, x = NULL, slope_FUN = slope, times = 100, alpha = 0.1, seed, ...)
``````

### Arguments

 `y` vector of observations of length n, or a matrix with n rows. `x` vector of predictor of length n, or a matrix with n rows. `...` ignored. `fast` Boolean. If true, `stats::.lm.fit()` will be used, which is 10x faster than `stats::lm()`. `slope_FUN` one of `slope()`, `slope_p()`, `slope_mk()` `times` The number of bootstrap replicates. `alpha` significant level, defalt 0.1 `seed` a single value, interpreted as an integer, or `NULL` (see ‘Details’).

### Value

• `slope` : linear regression coefficient

• `pvalue` : `⁠p-value <= 0.05`` means that corresponding ⁠`slope' is significant.

• `sd` : `⁠Std. Error⁠`

For `slope_boot`, slope is estimated in many times. The lower, mean, upper and standard deviation (sd) are returned.

### Examples

``````y <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69)
r <- slope(y)
r_p <- slope_p(y)
r_mk <- slope_mk(y)
r_boot <- slope_boot(y)
``````

rtrend documentation built on June 22, 2024, 11:39 a.m.