Having the following distributions (actual and predicted), Hist 1 to 3 (left to right). I would like to get a score ranging from 0-1 of how close the actual distribution is to be normal. I've found a couple of statistical normality tests: Shapiro-Wilk Test D’Agostino’s K^2 Test My DataSet is large therefore I've decided to check the skew and kurtosis statistics and got the following results: hist-1 Skewness is 0.028386209063816035 and Kurtosis is 2.4224694251429764 <-- Most normal hist-2 Skewness is …
This question does not ask for a formal solution or rephrasing, but for a practical implementation. That is why I am asking here and not on [cross-validate](https://clustering stats.stackexchange.com) Let us assume I have $y$ observations and a mixture model of $g$ Normally distributed components with mixing ratios $\lambda$ and I know their parameters $\theta$. How can I estimate only the ratios $\lambda$ and not the parameters $\theta$? So far I have only managed to estimate the entire mixture model, meaning …
I have some data I'm trying to analyze in SAS Studio (university edition). I am using the Distribution Analysis feature to try to test some data for normality. It gives me the following histogram: Skewness is approximately 2.934 and Kurtosis is approximately 9.013. I would have assumed based on that (and the fact that the shape of the histogram looks so different than the normal curve) that this is not normally distributed. However, my goodness-of-fit tests are: The Kolmogorov-Smirnov D …
Basically, I have created a linear model and am testing to verify the normality of my errors. As a result, I have used the qqPlot function from the car library and have gotten the graph that can be seen below as my output. Additionally 4 numbers were outputed (222, 160, 78, 113). My first question is, are these numbers meant to be outliers that are not consistent with the error terms being normally distributed? Secondly, what are the dashed lines …
I need to find a probability distribution to fit my data. My data has two important features, duration and activity count. Duration means how long one sequence lasts and activity count means the number of activities in one sequence. I want to draw a curve, which should be (but not definitely necessary) like normal distribution. The height of the peak is related to the activity count. The breadth of the peak (confidence area) is related to the duration. In my …