Operasi pada fungsi

library(mosaicCalc)

## Loading required package: mosaic

## Registered S3 method overwritten by 'mosaic':
##   method                           from   
##   fortify.SpatialPolygonsDataFrame ggplot2

## 
## The 'mosaic' package masks several functions from core packages in order to add 
## additional features.  The original behavior of these functions should not be affected by this.

## 
## Attaching package: 'mosaic'

## The following objects are masked from 'package:dplyr':
## 
##     count, do, tally

## The following object is masked from 'package:Matrix':
## 
##     mean

## The following object is masked from 'package:ggplot2':
## 
##     stat

## The following objects are masked from 'package:stats':
## 
##     binom.test, cor, cor.test, cov, fivenum, IQR, median, prop.test,
##     quantile, sd, t.test, var

## The following objects are masked from 'package:base':
## 
##     max, mean, min, prod, range, sample, sum

## Loading required package: mosaicCore

## 
## Attaching package: 'mosaicCore'

## The following objects are masked from 'package:dplyr':
## 
##     count, tally

## The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
## which was just loaded, will retire in October 2023.
## Please refer to R-spatial evolution reports for details, especially
## https://r-spatial.org/r/2023/05/15/evolution4.html.
## It may be desirable to make the sf package available;
## package maintainers should consider adding sf to Suggests:.
## The sp package is now running under evolution status 2
##      (status 2 uses the sf package in place of rgdal)

## 
## Attaching package: 'mosaicCalc'

## The following object is masked from 'package:stats':
## 
##     D

f <- rfun( ~ x, seed=579)
Zeros(f(x) - 10 ~ x, bounds(x=-4:4))

## # A tibble: 2 × 2
##         x      .output.
##     <dbl>         <dbl>
## 1 -2.92   -0.0000000344
## 2  0.0795 -0.00000118

slice_plot(f(x) ~ x, bounds(x=-4:4)) %>%
  gf_hline(yintercept = ~ 10, color="magenta")

library(mosaicCalc)
h <- rfun(~ x, seed=7293)
argM(h(x) ~ x, bounds(x=-5:5))

## # A tibble: 2 × 3
##        x .output. concavity
##    <dbl>    <dbl>     <dbl>
## 1 -1.68      1.93         1
## 2  0.173     8.25        -1

slice_plot(h(x) ~ x, bounds(x=-5:5))

better <- makeFun((guess + x/guess)/2 ~ guess)
better(1, x=55)

## [1] 28

better(28, x=55)

## [1] 14.98214

better(14.98214, x=55)

## [1] 9.326589

better(9.326589, x=55)

## [1] 7.611854

better(7.611854, x=55)

## [1] 7.418713

better(7.418713, x=55)

## [1] 7.416199

better(7.416199, x=55)

## [1] 7.416198

7.416198^2

## [1] 54.99999