Linear model: Least-Squares Fit

Schrick-Noah_CS-7863_Homework-4.R

@@ -1,4 +1,28 @@
 # Homework 4 for the University of Tulsa' s CS-7863 Network Theory Course
 # Degree Distribution
 # Professor: Dr. McKinney, Spring 2022
-# Noah Schrick - 1492657
+# Noah Schrick - 1492657
+
+library(igraph)
+library(igraphdata)
+data(yeast)
+g <- yeast
+
+################# Linear model: Least-Squares Fit #################
+g.hist <- hist(degree(g), freq=FALSE)
+g.seq <- 0:max(degree(g)) # x-axis
+g.breaks <- g.hist$breaks[-c(1,2)] # remove 0 and low degrees
+g.probs <- g.hist$density[-1] # make lengths match
+
+# Need to clean up probabilities that are 0
+nz.probs.mask <- g.probs!=0
+g.breaks.clean <- g.breaks[nz.probs.mask]
+g.probs.clean <- g.breaks[nz.probs.mask]
+
+plot(log(g.breaks.clean), log(g.probs.clean))
+g.fit <- lm(log(g.probs.clean)~log(g.breaks.clean))
+summary(g.fit)
+coef(g.fit)[2]
+
+
+################# Max-Log-Likelihood #################