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# PS239 - FALL 2006
# HINTS FOR PROBLEM SET 2
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# This code will show you how to transform your data into a matrix
# and give you some hints to use functions, adn to add an intercept to your regressions

#  0) First, load your libraries
library(MASS)
library(foreign)

#  1) Convert your data into a matrix

# Read the data into an object (my object is called "data.ps1")
data.ps1<-read.dta(file="W:/Teaching/Fall2006_PolSci239/ProblemSets/ProblemSet1/ME_households.dta")

# Note that data.ps1 is now a data frame
class(data.ps1)
# But we need our data to be a matrix, so we will use the "data.matrix()" function
# This function transforms a data frame into a matrix
# First, select the variables that you want to include in the matrix and create a smaller data frame
smaller.data.ps1<-data.frame(data.ps1$c411a,data.ps1$c414,data.ps1$c415)
# Now that you have created the smaller data frame, go ahead and transform this data frame into a matrix
matrix1<-data.matrix(smaller.data.ps1)
dim(matrix1)
# So "matrix1" is a 1895x3 matrix that contains the variables c411a,c414, and c415

# Now you are ready to use matrix1 to do matrix computations

################ HOW TO ADD AND INTERCEPT  ###################################################
# You'll need to add an intercept to your regressions
# THis means that your X matrix must have a column of ones
# To add a column of ones to our data frame do the following
rep(1,nrow(X))  # This creates a vector of lenght equal to the number of rows of X, adn puts a 1 in all the entries
# So try
ones<-rep(1,nrow(matrix1))
# Now create a data frame with this additional variable
smaller.data.ps1.intercept<-data.frame(ones,smaller.data.ps1)
smaller.data.ps1.intercept
dim(smaller.data.ps1.intercept)   # Note that we have an extra column of ones
# And now transfrom this into a matrix
matrix1<-data.matrix(smaller.data.ps1.intercept)
# Done!!!!

################ FUNCTION  HINTS ###################################################

# We've seen in section how to use a function to perform matrix algebra operations
# Just remember that if you use a function with many arguments
# such as "myfunction<-function(x,y,z,w)"
# when you pass the arguments to the function, you either respect the order
# or use the names of the arguments
# So myfunction(1,2,3,4) or myfunction(x=1,y=2,z=3,w=4) are equivalent
# If you use the names, as in the latter case, the order does not matter
# so myfunction(x=1,y=2,z=3,w=4) is the same as myfunction(x=1,w=4,y=2,z=3)
# But if you do not specify the names, then the order does matter
# hence myfunction(1,2,3,4) is different from myfunction(1,4,2,3)