[Uwgarp-commits] r13 - pkg/GARPFRM/sandbox

[noreply at r-forge.r-project.org]

Author: rossbennett34
Date: 2013-11-23 19:27:59 +0100 (Sat, 23 Nov 2013)
New Revision: 13

Added:
   pkg/GARPFRM/sandbox/regression_example.R
Log:
Adding regression example to sandbox

Added: pkg/GARPFRM/sandbox/regression_example.R
===================================================================
--- pkg/GARPFRM/sandbox/regression_example.R	                        (rev 0)
+++ pkg/GARPFRM/sandbox/regression_example.R	2013-11-23 18:27:59 UTC (rev 13)
@@ -0,0 +1,55 @@
+# regression example
+
+library(GARPFRM)
+
+# The returns data includes weekly returns
+data(returns)
+
+# Get the weekly returns of AAPL and SPY from the returns object
+AAPL.ret <- returns[, "AAPL"]
+SPY.ret <- returns[, "SPY"]
+
+# Plot the AAPL vs. SPY returns
+plot(x=coredata(SPY.ret), y=coredata(AAPL.ret), 
+     xlab="SPY returns", ylab="AAPL returns")
+
+# Fit the linear regression model
+model.fit <- lm(AAPL.ret ~ SPY.ret)
+class(model.fit)
+
+# The print method displays the call and the coefficients of the model
+print(model.fit)
+
+# Accessor methods for the lm object
+coef(model.fit)
+fitted(model.fit)
+resid(model.fit)
+rstandard(model.fit)
+
+# The summary method displays much more information
+model.summary <- summary(model.fit)
+class(model.summary)
+names(model.summary)
+
+print(model.summary)
+
+coef(model.summary)
+model.summary$sigma
+model.summary$r.squared
+model.summary$adj.r.squared
+
+# Predict method
+predict(object=model.fit, newdata=data.frame(SPY.ret=c(-0.1, 0, 0.1)))
+model.ci <- predict(object=model.fit, interval="confidence")
+model.pi <- predict(object=model.fit, interval="prediction")
+
+# Plot AAPL vs SPY returns
+plot(x=coredata(SPY.ret), y=coredata(AAPL.ret), 
+     xlab="SPY returns", ylab="AAPL returns")
+abline(model.fit, col="red")
+lines(x=coredata(SPY.ret), y=model.ci[, "upr"], col="blue", lty=1)
+lines(x=coredata(SPY.ret), y=model.ci[, "lwr"], col="blue", lty=1)
+lines(x=coredata(SPY.ret), y=model.pi[, "upr"], col="red", lty=2)
+lines(x=coredata(SPY.ret), y=model.pi[, "lwr"], col="red", lty=2)
+
+plot(resid(model.fit), type="h")