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tools & techniques for analysis

ml machine learning, data mining, deep learning, ai
da probability, statistics, data analysis, business intellligence
nt notes, tips, tricks, usage of tools
ts time series, signal processing
bk books, course notes, reference material
bz project, management, retail, customer, marketing, business
cd code, experiments, algorithms, software
cs case studies
ac academics, articles, research papers

Syntax highlight test

# Goal: Some of the standard tests

# A classical setting --
x <- runif(100, 0, 10)                  # 100 draws from U(0,10)
y <- 2 + 3*x + rnorm(100)               # beta = [2, 3] and sigma is 1
d <- lm(y ~ x)
# CLS results --
summary(d)

library(sandwich)
library(lmtest)
# Durbin-Watson test --
dwtest(d, alternative="two.sided")
# Breusch-Pagan test --
bptest(d)
# Heteroscedasticity and autocorrelation consistent (HAC) tests
coeftest(d, vcov=kernHAC)

# Tranplant the HAC values back in --
library(xtable)
sum.d <- summary(d)
xtable(sum.d)
sum.d$coefficients[1:2,1:4] <- coeftest(d, vcov=kernHAC)[1:2,1:4]
xtable(sum.d)

Latex test:

$${\sqrt {n}}\left(\left({\frac {1}{n}}\sum _{i=1}^{n}X_{i}\right)-\mu \right)\ {\xrightarrow {d}}\ N\left(0,\sigma ^{2}\right)$$