Dosen Pembimbing : Prof. Dr. Suhartono, M.Kom
Lembaga : Universitas Islam Negeri Maulana Malik Ibrahim Malang
Jurusan : Teknik Informatika
Fakultas : Sains dan Teknologi
library(mosaicCalc)
## Loading required package: mosaicCore
## Loading required package: Deriv
## Loading required package: Ryacas
##
## Attaching package: 'Ryacas'
## The following object is masked from 'package:stats':
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## integrate
## The following objects are masked from 'package:base':
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## %*%, diag, diag<-, lower.tri, upper.tri
## Registered S3 method overwritten by 'mosaic':
## method from
## fortify.SpatialPolygonsDataFrame ggplot2
##
## Attaching package: 'mosaicCalc'
## The following object is masked from 'package:stats':
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## D
library(mosaic)
##
## 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':
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## count, do, tally
## The following object is masked from 'package:Matrix':
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## mean
## The following object is masked from 'package:ggplot2':
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## stat
## The following objects are masked from 'package:stats':
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## binom.test, cor, cor.test, cov, fivenum, IQR, median, prop.test,
## quantile, sd, t.test, var
## The following objects are masked from 'package:base':
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## max, mean, min, prod, range, sample, sum
Utils <- read.csv("http://www.mosaic-web.org/go/datasets/utilities.csv")
gf_point(ccf ~ temp, data = Utils) %>%
gf_labs(y = "Natural gas usage (ccf/month)",
x = "Average outdoor temperature (F)")
f <- fitModel(ccf ~ A * temp + B, data = Utils)
gf_point(ccf ~ temp, data = Utils) %>%
slice_plot(f(temp) ~ temp)
f2 <- fitModel(
ccf ~ A * temp + B + C *sqrt(temp),
data = Utils)
gf_point(
ccf ~ temp, data = Utils) %>%
slice_plot(f2(temp) ~ temp)
Hondas <- read.csv("http://www.mosaic-web.org/go/datasets/used-hondas.csv")
head(Hondas)
## Price Year Mileage Location Color Age
## 1 20746 2006 18394 St.Paul Grey 1
## 2 19787 2007 8 St.Paul Black 0
## 3 17987 2005 39998 St.Paul Grey 2
## 4 17588 2004 35882 St.Paul Black 3
## 5 16987 2004 25306 St.Paul Grey 3
## 6 16987 2005 33399 St.Paul Black 2
carPrice3 <- fitModel(
Price ~ A + B * Age + C * Mileage + D * Age * Mileage +
E * Age^2 + F * Mileage^2 + G * Age^2 * Mileage +
H * Age * Mileage^2,
data = Hondas)
gf_point(Mileage ~ Age, data = Hondas, fill = NA) %>%
contour_plot(
carPrice3(Age=Age, Mileage=Mileage) ~ Age + Mileage)