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