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jonnyrobbie/metro.csv

Last active December 27, 2016 14:58
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R script for simple OLS
Raw
metro.csv
Year M_1_length_of_routes M_2_vehicles M_3_passengers M_4_avg_speed M_5_place_km S_6_length_of_routes S_7_vehicles S_8_passengers S_9_avg_speed S_10_place_km T_11_passengers T_12_Prague_population T_13_avg_income_Prague
2001 50.1 490 442448000 35.36 7132399000 2703.8 2266 661891000 22.54 10359943000 1104339000 1160118 18442
2002 50.1 491 416516000 35.36 6443208000 2725.7 2308 699093000 22.71 11075738000 1115609000 1161938 19926
2003 50.1 514 458642000 35.7 7290246000 2731.1 2290 672146000 22.95 10720017000 1130788000 1165581 21114
2004 54 490 496013000 34.6 8215418000 2677.3 2221 664519000 22.7 10661613000 1160532000 1170571 22204
2005 54 420 515098000 34.6 8632642000 2643.8 2149 632302000 22.9 10661296000 1147400000 1181610 23367
2006 54.9 555 531239000 34.6 8703277000 2682.7 2161 650166000 22.35 10702364000 1181405000 1188126 25001
2007 54.9 567 537266000 35.8 8721653000 2655.9 2138 655660000 22.25 10690456000 1192926000 1212097 26566
2008 59.4 576 596893000 35.51 9801991000 2452.6 2094 664946000 22.05 10894615000 1261839000 1233211 29031
2009 59.4 610 584880000 35.48 9797216000 2363 2126 651593000 22.23 10865571000 1236473000 1249026 30105
2010 59.4 635 578515000 35.48 9899274000 2346.8 2075 645420000 22.52 10926624000 1223935000 1257158 29933
2011 59.4 685 530493000 35.65 10151225000 2337.8 2153 592478000 22.21 11228244000 1122971000 1241664 31359
2012 59.4 730 589165000 35.65 10030824000 2216.9 2134 639718000 22.28 11158585000 1216529000 1246780 31842
2013 59.4 730 583867000 35.65 9813548000 2188.7 2166 648817000 22.21 10812352000 1232684000 1243201 31300
2014 59.4 730 450136000 35.65 9672501000 2196.2 2090 704362000 22.22 10823639000 1162593000 1259079 31985
2015 65.4 730 456820000 35.65 10272709000 2141.1 2044 706841000 22.12 10940362000 1171723000 1267449 32489
Raw
metro_ols.R
#https://www.reddit.com/r/econometrics/comments/5kgcq2/simple_ols_model_for_school_project_but_the/
require(reshape)
require(ggplot2)
require(pls)
#load data
setwd("~/RWD")
metro <- read.csv("metro.csv", header=T, row.names=1)
#OLS
fullModel <- lm(M_3_passengers~., data=metro)
partialModel <- lm(M_3_passengers~S_7_vehicles+S_8_passengers+T_11_passengers, data=metro)
almostFullModel <- lm(M_3_passengers~.-T_11_passengers, data=metro)
summary(fullModel)
summary(partialModel)
summary(almostFullModel)
#correlation
corMatrix <- round(cor(metro), 2)
meltedCor <- melt(corMatrix)
corPlot <- ggplot(data=meltedCor, aes(X1, X2, fill=value)) +
geom_tile() +
scale_fill_gradient2(low="red", mid="white", high="blue", limit = c(-1,1)) +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
geom_text(aes(label = value), color = "black", size = 4)
corPlot
#PCA
pcaMetro <- prcomp(metro)
scree <- ggplot(data=as.data.frame(pcaMetro$sdev), aes(1:13, pcaMetro$sdev)) +
geom_line() +
geom_point()
scree
pcrMetro <- pcr(M_3_passengers~.-T_11_passengers, data=metro, ncomp=5)
summary(pcrMetro)
str(pcrMetro)
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