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The standard approaches (Sturges, Freedman/Diaconis, etc.) generally work fine but those don't work well for some distributions. …

Bernardo and Smith (1994, Sec. 4.7) discuss a result of Diaconis and Freedman (1980) on finite exchangeable sequences showing that if the considered sequence can be extended to an exchangeable sequence …

I used minitab to draw a normal distribution histogram and saw that the number of bins in that graph doesn't follow any rules to calculate bin size that I know of (sturge, square-root, rice, freedman-diaconis …

properties of Bayesian updating --- e.g., looking at the "frequentist consistency" of Bayesian analysis under correct or incorrect model specification in a range of model classes (see e.g., Berk 1970, Diaconis … and Freedman 1986, Barron, Schervish and Wasserman 1999, Ghosal, Ghosh and van der Vaart 2000, Shen and Wasserman 2001, Walker 2009, Shalizi 2009). …

parametric form and then you would have a parametric binary regression model, or you might simply assume some simple smoothness properties and decide to use a nonparametric binary regression model (see e.g., Diaconis … and Freedman 1993). …

I am aware of Sturge’s and Freedman-Diaconis rules. … I am looking for an equation/ test, similar to Sturge’s and Freedman-Diaconis rules, that can do this. …

If you look at R's hist.default function, the nclass.FD function computes the number of bins for Freedman-Diaconis rule. …

Freedman-Diaconis, prescribes a formula for determining a bin width that minimizes the integral of squared error between the resulting histogram and "underlying/true" probability distribution. … Shimazaki-Shinomoto is similar in flavour to Freedman-Diaconis. Variations on the histogram is a bit different from the two above, and is related to creating histograms with "equal-area" per bin. …

Currently, I'd like to use the Freedman-Diaconis rule for determine bin widths: $h=2\times\text{IQR}\times N^{-1/3}$ (where $h$ is the bin width). … The problem with this is that each dataset would have a different IQR, and thus a different recommendation for the bin width according to Freedman-Diaconis. …

Two other rules in common use include 'Freedman-Diaconis' and 'square root'. … log2(10000) [1] 13.28771 set.seed(606) x = rexp(10000, .01) hist(x) By contrast, the Freedman-Diaconis rule suggests between 85 and 90 bins. …

hist(x1, col="skyblue2") # 1 hist(x, col="skyblue2") # 2 hist(x, br=3*b, col="skyblue2") # 3 par(mfrow=c(1,1)) # return to single-panel plots I'm not claiming that R uses the Freedman-Diaconis …

For discretization, I'm using Freedman-Diaconis rule which computes the optimal number of bins which will be given input to KBinsDiscretizer. … Freedman-Diaconis' rule states that, $$ \text{bin width}, h=2\frac{\operatorname{IQR}(x)}{n^{1/3}} $$ $$ \text{number of bins}, k = \frac{range(x)}{h} $$ The column has $32561$ values. …

There is another useful extension by Diaconis and Freedman (1980) that establishes a representation theorem for cases of finite exchangeability --- roughly speaking, in this case the values are "almost …

Diaconis, Freedman (1980): Finite exchangeable sequences, Ann. Prob. 8, 745 https://doi.org/10.1214/aop/1176994663. Diaconis, Freedman (1981): On the statistics of vision: The Julesz conjecture, J. … Diaconis, Janson (2008): Graph limits and exchangeable random graphs, Rend. Matematica 28, 33 http://www1.mat.uniroma1.it/ricerca/rendiconti/ARCHIVIO/2008(1)/33-61.pdf. …

Freedman–Diaconis rule or the square-root-$N$ rule, and get the count number for each bin centre and then fit the function to these coordinates. …