Hannan , On stochastic complexity and nonparametric density estimation. Biometrika 75 He and G. Meeden , Selecting the number of bins in a histogram: A decision theoretic approach. Inference 61 Herrick , G. Nason and B. Silverman , Some new methods for wavelet density estimation. Sankhya, Series A 63 Jones , On two recent papers of Y. Kanazawa , Hellinger distance and Akaike's information criterion for the histogram.
Le Cam and G. Second Edition. Rissanen , Stochastic complexity and the MDL principle. Rudemo , Empirical choice of histograms and kernel density estimators. Scott , On optimal and databased histograms. Biometrika 66 Sturges , The choice of a class interval. Taylor , Akaike's information criterion and the histogram. Bayesian Blocks for Histograms. Sign up to join this community. The best answers are voted up and rise to the top. Stack Overflow for Teams — Collaborate and share knowledge with a private group.
Create a free Team What is Teams? Learn more. Calculating optimal number of bins in a histogram Ask Question. Asked 11 years, 3 months ago. Active 6 months ago. Viewed k times. Improve this question. Tony Stark Tony Stark 1, 2 2 gold badges 8 8 silver badges 5 5 bronze badges. Add a comment. Active Oldest Votes. Improve this answer. Rob Hyndman Rob Hyndman Look for 1st quartile and 3rd quartile and the difference is IQR.
IQR already comes with R so you can use it. FD did not exist nine years ago. Show 11 more comments. Harvey Motulsky Harvey Motulsky I'm not sure if this is the same thing: toyoizumilab. They also mention that code in R is available on request. Girardi Girardi 1 1 silver badge 4 4 bronze badges. And yes its more expensive since you pick a range for the number of bins and you must make a histogram for each and then compute a cost, then pick the most minimal costing one.
Community Bot 1. Ian Turner Ian Turner 3 3 silver badges 13 13 bronze badges. Benjamin Bannier Benjamin Bannier 6 6 silver badges 10 10 bronze badges. But the usage of these two differ significantly. Bar Graphs are used to compare different categories of data , and the scaling is applied to measure the extreme values of the categories within one chart.
Columns can be placed vertically or horizontally. If they are vertical, we speak about a column chart , where the vertical axis contains the scale while the horizontal axis shows the categories like: age group, year, months, etc. Major disadvantage of this chart is that naming of the columns is impossible if there are too many categories.
If you want to see the development of data within your chart, histograms will be your choice. In a histogram, the horizontal axis shows frequency and vertically you can see the interval or time range values. This way, you can get a picture of data distribution and you can clearly see the outliers in your set of data. If you have a set of data values , you probably want to share this information with your boss or co-workers to make better business decisions based on the information contained in these data.
Instead of showing the numbers it is better if you use visuals. You should share the information in a compact way because nobody wants to read numeric values one by one. Create Histogram with AnswerMiner. Sign up for free. The mean value Almost all real-world data has outliers, so the mean value can be very misleading. Interquartile range IQR The above listed statistical values are very useful, but always keep in mind to use them in a context with other information , not just as a standalone metric.
These numeric summarizing techniques do not include any information about spikes , or the shape of the distribution.
0コメント