R
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r<-matrix(nrow =10,ncol = 10)
for(i in 1:10){
for(j in 1:10)
r[i,j]<-covBeta[i,j]/(sqrt(covBeta[i,i])*sqrt(covBeta[j,j]))}
r
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[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.00000000 -0.06053935 0.00914841 -0.28334204 -0.03304466 0.04233039 -0.2883136
[2,] -0.06053935 1.00000000 0.76117459 0.63132117 0.10655347 0.72992413 0.1190900
[3,] 0.00914841 0.76117459 1.00000000 0.69220144 -0.26424621 0.59208828 0.0639940
[4,] -0.28334204 0.63132117 0.69220144 1.00000000 -0.22886901 0.47795015 0.3342855
[5,] -0.03304466 0.10655347 -0.26424621 -0.22886901 1.00000000 -0.02366330 0.1391050
[6,] 0.04233039 0.72992413 0.59208828 0.47795015 -0.02366330 1.00000000 0.0573803
[7,] -0.28831363 0.11908997 0.06399400 0.33428549 0.13910500 0.05738030 1.0000000
[8,] 0.38642324 -0.02895360 -0.13894158 -0.32861926 -0.25030979 0.03728372 -0.5001870
[9,] -0.94875453 -0.08563015 -0.15591018 0.09365267 -0.03454892 -0.09369497 0.1023999
[10,] -0.46881141 0.08848222 -0.06488233 0.22536209 0.09624905 0.09598542 0.5044800
[,8] [,9] [,10]
[1,] 0.38642324 -0.94875453 -0.46881141
[2,] -0.02895360 -0.08563015 0.08848222
[3,] -0.13894158 -0.15591018 -0.06488233
[4,] -0.32861926 0.09365267 0.22536209
[5,] -0.25030979 -0.03454892 0.09624905
[6,] 0.03728372 -0.09369497 0.09598542
[7,] -0.50018700 0.10239990 0.50448003
[8,] 1.00000000 -0.19482468 -0.31455212
[9,] -0.19482468 1.00000000 0.28444927
[10,] -0.31455212 0.28444927 1.00000000
R
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install.packages("car")
library(carData)
Anova(lm1,type = "III")
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Anova Table (Type III tests)
Response: y
Sum Sq Df F value Pr(>F)
(Intercept) 998 1 0.0066 0.9360967
x1 23314547 1 153.7558 3.969e-11 ***
x2 4561056 1 30.0795 1.927e-05 ***
x3 2662593 1 17.5594 0.0004121 ***
x4 21 1 0.0001 0.9907203
x5 9377500 1 61.8432 1.083e-07 ***
x6 89586 1 0.5908 0.4506651
x7 17700 1 0.1167 0.7360055
x8 54295 1 0.3581 0.5559828
x9 17149 1 0.1131 0.7399858
Residuals 3184305 21
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R
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r<-cor(data3_1)
r
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x1 x2 x3 x4 x5 x6 x7 x8
x1 1.0000000 0.22714089 0.6117634 0.21301742 0.7872537 0.69676095 0.6970034 -0.16339935
x2 0.2271409 1.00000000 0.3053681 0.64622334 0.4704869 0.46044177 0.6146573 0.14367061
x3 0.6117634 0.30536809 1.0000000 0.58409947 0.7364894 0.53927001 0.7768628 -0.17839396
x4 0.2130174 0.64622334 0.5840995 1.00000000 0.4881049 0.38109255 0.6513102 0.07004622
x5 0.7872537 0.47048687 0.7364894 0.48810487 1.0000000 0.74689394 0.8141689 -0.10432612
x6 0.6967609 0.46044177 0.5392700 0.38109255 0.7468939 1.00000000 0.7801488 -0.01790576
x7 0.6970034 0.61465733 0.7768628 0.65131022 0.8141689 0.78014879 1.0000000 -0.01989850
x8 -0.1633994 0.14367061 -0.1783940 0.07004622 -0.1043261 -0.01790576 -0.0198985 1.00000000
x9 -0.3755017 0.01334004 -0.3247017 -0.10969051 -0.3743180 -0.49913442 -0.2623661 -0.13009092
y 0.9022762 0.51172104 0.7811370 0.49423568 0.9414255 0.78487674 0.8733947 -0.13026967
x9 y
x1 -0.37550174 0.9022762
x2 0.01334004 0.5117210
x3 -0.32470168 0.7811370
x4 -0.10969051 0.4942357
x5 -0.37431801 0.9414255
x6 -0.49913442 0.7848767
x7 -0.26236608 0.8733947
x8 -0.13009092 -0.1302697
x9 1.00000000 -0.3614779
y -0.36147795 1.0000000
R
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install.packages("corpcor")
library(corpcor)
pcor<-cor2pcor(r)
pcor
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[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.00000000 -0.76117459 -0.63132117 -0.106553471 -0.72992413 -0.1190900 0.02895360
[2,] -0.76117459 1.00000000 -0.69220144 0.264246208 -0.59208828 -0.0639940 0.13894158
[3,] -0.63132117 -0.69220144 1.00000000 0.228869013 -0.47795015 -0.3342855 0.32861926
[4,] -0.10655347 0.26424621 0.22886901 1.000000000 0.02366330 -0.1391050 0.25030979
[5,] -0.72992413 -0.59208828 -0.47795015 0.023663295 1.00000000 -0.0573803 -0.03728372
[6,] -0.11908997 -0.06399400 -0.33428549 -0.139105005 -0.05738030 1.0000000 0.50018700
[7,] 0.02895360 0.13894158 0.32861926 0.250309793 -0.03728372 0.5001870 1.00000000
[8,] 0.08563015 0.15591018 -0.09365267 0.034548922 0.09369497 -0.1023999 0.19482468
[9,] -0.08848222 0.06488233 -0.22536209 -0.096249054 -0.09598542 -0.5044800 0.31455212
[10,] 0.93799379 0.76738247 0.67482266 -0.002568401 0.86400751 0.1654203 0.07434895
[,8] [,9] [,10]
[1,] 0.08563015 -0.08848222 0.937993789
[2,] 0.15591018 0.06488233 0.767382474
[3,] -0.09365267 -0.22536209 0.674822662
[4,] 0.03454892 -0.09624905 -0.002568401
[5,] 0.09369497 -0.09598542 0.864007510
[6,] -0.10239990 -0.50448003 0.165420303
[7,] 0.19482468 0.31455212 0.074348952
[8,] 1.00000000 -0.28444927 -0.129479136
[9,] -0.28444927 1.00000000 0.073188710
[10,] -0.12947914 0.07318871 1.000000000