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| # | |
| # noisey-data.R, 24 Mar 20 | |
| # Data from: | |
| # Example | |
| # | |
| # Example from: | |
| # Evidence-based Software Engineering: based on the publicly available data | |
| # Derek M. Jones | |
| # | |
| # TAG example_model ratio-test | |
| source("ESEUR_config.r") | |
| library("plyr") | |
| plot_layout(2, 2, max_height=12) | |
| par(mar=MAR_default-c(0.6, -1, 0.8, 1)) | |
| pal_col=rainbow(3) | |
| fit_and_plot=function(x, y) | |
| { | |
| # nls_mod = nls(y ~ a+b*x^power, start = list(a=1e5, b=1, power = 2), | |
| # trace=TRUE) | |
| # summary(nls_mod) | |
| p_mod=glm(y ~ x, family=poisson) | |
| l_mod=glm(y ~ log(x), family=poisson) | |
| q_mod=glm(y ~ I(x^2)) | |
| # print(summary(l_mod)) | |
| # print(summary(p_mod)) | |
| # print(summary(q_mod)) | |
| plot(x, y, log="y", col=pal_col[2], | |
| xlab="X", ylab="Y\n") | |
| # pred=predict(l_mod, newdata=data.frame(x=1:100), type="response") | |
| # lines(pred, col=pal_col[1]) | |
| pred=predict(p_mod, newdata=data.frame(x=1:100), type="response") | |
| lines(pred, col=pal_col[1]) | |
| pred=predict(q_mod, newdata=data.frame(x=1:100)) | |
| lines(pred, col=pal_col[3]) | |
| } | |
| fit_peaks=function(x, y) | |
| { | |
| peak_vals=ddply(data.frame(x, y), .(x), | |
| function(df) | |
| data.frame(x=df$x[1], | |
| y=tail(sort(df$y), n=3)) | |
| ) | |
| p_mod=glm(y ~ x, data=peak_vals, family=poisson) | |
| l_mod=glm(y ~ log(x), data=peak_vals, family=poisson) | |
| q_mod=glm(y ~ I(x^2), data=peak_vals) | |
| # print(summary(l_mod)) | |
| # print(summary(p_mod)) | |
| # print(summary(q_mod)) | |
| # pred=predict(l_mod, newdata=data.frame(x=1:100), type="response") | |
| # lines(pred, col=pal_col[1]) | |
| pred=predict(p_mod, newdata=data.frame(x=1:100), type="response") | |
| lines(pred, col=pal_col[1]) | |
| pred=predict(q_mod, newdata=data.frame(x=1:100)) | |
| lines(pred, col=pal_col[3]) | |
| } | |
| ratio_test=function(x, y) | |
| { | |
| plot(0, type="n", log="y", | |
| xlab="X", ylab="Ratio\n\n", | |
| xlim=range(x), ylim=c(1e-6, 100)) | |
| points(x, y/exp(x/5), col=pal_col[2]) | |
| points(x, y/x^2, col=pal_col[3]) | |
| points(x, y/x^3, col=pal_col[1]) | |
| } | |
| # Generate data for a quadratic plus noise | |
| x = rep(seq(10, 100, by=10), 25) | |
| # Take abs just in case a large negative value is generated | |
| y = abs(x^2 + 1e3*(5+rnorm(length(x)))) | |
| fit_and_plot(x, y) | |
| fit_peaks(x, y) | |
| ratio_test(x, y) | |
| y = abs(x^2 + 1e2*(5+rnorm(length(x)))) | |
| fit_and_plot(x, y) | |
| # fit_peaks(x, y) | |
| ratio_test(x, y) | |