Incident times follow a von Mises distribution centered near 5:30pm.
One goal of the SARBayes project is to forecast the probability of survival for lost persons. Such models could be useful in deciding to continue searching, and researchers making motion models can use survival predictions when generating probability maps of the lost person's location. We are analyzing data from the International Search & Rescue Incident Database (ISRID) to describe the probability of survival as a function of various features, such as age or temperature.
Continue reading "Fitting Incident Time to a Distribution"
A logical extension of the Distance Rings model is to fit a smooth function to the distribution of data found in ISRID. Examining the Euclidean Distance data for different categories, it was found that a lognormal curve roughly captured the shape of the data. The Log-Normal (LN) is a two parameter distribution which assumes that the logarithm of your data follows a normal distribution. The probability density function of the LN curve is given by, where are the mean and standard deviation of the logarithm of distance.
Continue reading "The Lognormal Distance Model"
An abstract just crossed my desk that I'd love to share. Briefly, adding meaningless math to your academic paper inordinately impresses humanities PhDs. The author does not say whether this also works in pickup lines, so there's room for follow-on research.
Continue reading "The nonsense math effect"