Nama : Muhammad Nur Ramadhan

NIM : 230605110077

KELAS : C KALKULUS

DOSEN PENGAMPU : Prof. Dr. SUHARTONO, M.Kom

LEMBAGA : UIN MAULANA MALIK IBRAHIM MALANG

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
Zeros(x^3 - 6 ~ x, bounds(x=c(1,6)))
## # A tibble: 1 × 2
##       x    .output.
##   <dbl>       <dbl>
## 1  1.82 0.000000203
## # A tibble: 1 × 2
##       x    .output.
##   <dbl>       <dbl>
## 1  1.82 0.000000203
f <- rfun(~ x, 3215)
argM(f(x) ~ x, bounds(x = -5:5))
## # A tibble: 2 × 3
##       x .output. concavity
##   <dbl>    <dbl>     <dbl>
## 1  1.03   -26.5          1
## 2 -2.95     3.80        -1
## # A tibble: 2 × 3
##       x .output. concavity
##   <dbl>    <dbl>     <dbl>
## 1  1.03   -26.5          1
## 2 -2.95     3.80        -1
Iterate(2*x*(1-x) ~ x, x0=0.3, n=10)
##     n         x
## 1   0 0.3000000
## 2   1 0.4200000
## 3   2 0.4872000
## 4   3 0.4996723
## 5   4 0.4999998
## 6   5 0.5000000
## 7   6 0.5000000
## 8   7 0.5000000
## 9   8 0.5000000
## 10  9 0.5000000
## 11 10 0.5000000
##     n         x
## 1   0 0.3000000
## 2   1 0.4200000
## 3   2 0.4872000
## 4   3 0.4996723
## 5   4 0.4999998
## 6   5 0.5000000
## 7   6 0.5000000
## 8   7 0.5000000
## 9   8 0.5000000
## 10  9 0.5000000
## 11 10 0.5000000
Iterate(3.2*x*(1-x) ~ x, x0=0.3, n=50) |> tail()
##     n         x
## 46 45 0.5130445
## 47 46 0.7994555
## 48 47 0.5130445
## 49 48 0.7994555
## 50 49 0.5130445
## 51 50 0.7994555
##     n         x
## 46 45 0.5130445
## 47 46 0.7994555
## 48 47 0.5130445
## 49 48 0.7994555
## 50 49 0.5130445
## 51 50 0.7994555
Iterate(4.0*x*(1-x) ~ x, x0=0.3, n=5000) |> tail()
##         n          x
## 4996 4995 0.56824790
## 4997 4996 0.98136889
## 4998 4997 0.07313595
## 4999 4998 0.27114833
## 5000 4999 0.79050766
## 5001 5000 0.66242119
##         n          x
## 4996 4995 0.56824790
## 4997 4996 0.98136889
## 4998 4997 0.07313595
## 4999 4998 0.27114833
## 5000 4999 0.79050766
## 5001 5000 0.66242119