SOME NOTES ON R FACILITIES FOR USE IN ASSIGNMENT 2


Sorting:

   sort(x)             Takes a vector and returns it in sorted order

   order(x)            Takes a vector and returns the vector of indexes
                       that would make it sorted.  So x[order(x)] produces
                       the same result as sort(x)

Covariance matrices:

   cov(X)              Returns the sample covariance matrix of data in X,
                       which has one case per line and one column per variable.

Logistic regression:

   m = glm(y~X,family="binomial",maxit=1000)  

       Fits a logistic regression model for the binary responses in the
       vector y, using the covariates in the matrix X.  An intercept term
       is also included in the model (so there's no need for X to have a
       column of all 1s).  The result is a "model" object that can be used
       with the functions below.  The "maxit" option tells it to try harder
       to find the solution (the default is a bit small).

   print(m)  OR   print(summary(m))

       Displays information on a model fit with glm.

   coef(m)

       Returns the regression coefficients found by fitting a model with glm.
       The first coefficient is the intercept.


Plotting:

You can make scatterplots with classes in different colours (based on
0/1 class values) with a command like this:

   plot(x.train[,1],x.train[,2],pch=20,col=c("blue","red")[1+t.train])