Questions tagged [histogram]

A histogram is a graphical representation of the frequencies of a continuous variable. The variable is divided into bins and a bar is drawn for each bin, proportional to its frequency in the data.

148 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
5
votes
1answer
1k views

Bhattacharyya distance for three histograms

There is a paper “Auto White Balance Based on the Similarity of Chromaticity Histograms” mention about automatic white balance. One of the key point of this algorithm is how to measure the similarity ...
5
votes
1answer
4k views

Linear mixed effects models: what to do when the residual QQ-plot looks non-normal?

I have four linear mixed effect models of similar structure: ...
4
votes
0answers
1k views

Where is the maximum bias and variance in a histogram as non-parametric density estimator?

I am a little bit confused about bias and variance of non-parametric density estimators and hope you can help me. Assuming a constant bandwidth and sample size, I am wondering at which points of the ...
3
votes
0answers
367 views

Who invented the “Histogram”?

While going through Wikipedia's article History of statistics I found In 1786 William Playfair (1759-1823) introduced the idea of graphical representation into statistics. He invented the line chart, ...
3
votes
0answers
47 views

What methods are there for estimating distributions based on histograms?

I recently worked on a consulting project where a client wanted to estimate gamma and weibull distributions based purely on histograms rather than raw-data. I have never worked with problems like that ...
3
votes
0answers
130 views

How to compute optimal binning for two histograms

I am plotting two histograms on top of one another (using matplotlib, but that is tangential to my question). My current approach is to compute the mean of the optimal bin widths for each histogram ...
3
votes
0answers
112 views

Is it sensible to calculate posterior by dividing histograms?

I have some data I want to classify as $A$ or $\bar{A}$ (not-$A$) based on two metric features $M$ and $P$. It seems straight-forward to calculate a posterior probability, that a given combination of $...
3
votes
0answers
91 views

Given the number of Bins, what is the formula for estimating bin height in a 2D Histogram

Given the number of Bins, what is the formula for estimating bin height in a 2D Histogram in binormal distribution?
3
votes
0answers
262 views

Make 2D color histogram with uniform distribution (Likert scale)

UPDATE: I've been told that I cannot specifically ask for help in regards to the programming (MatLab and PR Tools), but instead should seek help for general techniques. So that's what I'm doing. Long ...
3
votes
0answers
159 views

clustering for histogram shapes

I am trying to get a start on a clustering problem. The sample data is trade volume at a particular price. Some notes about the data: number of bins vary from sample to sample (larger price range ...
3
votes
0answers
42 views

10% dip in February for metrics that count?

February usually has 28 days, unlike it's neighbors January and March which have 31. It seems that most countable things will exhibit, on average, a 10% dip in February for the missing 3 days. This ...
3
votes
0answers
2k views

Combining errors in a histogram (binned data)

I'm processing some data that requires binning before it goes through a regression algorithm. The script is in Python and uses the Numpy histogram function, but ...
2
votes
0answers
101 views

Least Square Cross Validation for Density Estimation with Histograms

In a 1981 paper by Rudemo an easy to compute expression for the integrated squared error of a histogram relative to the true distribution is derived (Eq. 2.8 of the paper and the last equation in this ...
2
votes
1answer
383 views

Error Bars for Histogram with Uncertain Data

Context I have a set of data points $\{x_1, \dots, x_N \}$ along with the respective measurement uncertainties $\{\epsilon_1, \dots, \epsilon_N\}$ in them ($N \approx 100$). These data are basically ...
2
votes
0answers
273 views

How to plot a marginal histogram correctly? Why is my plot different to the one in a textbook?

Chapter 1 of "Machine Learning - A Probabilistic Perspective" by Kevin Patrick Murphy gives this figure (fig_1), and says this is a pairwise scatter plot on iris dataset. The diagonal plots the ...
2
votes
0answers
110 views

A comparison of the global optimal binwidth and local optimal binwidth of the histogram estimator

Suppose we have $X_1, \dots, X_n$ to be an i.i.d sample with unknown pdf $f(x)$ and cdf $F(x)$, and define $\hat{f} (x)$ to be the histogram estimator. We also define its Mean Integrated Square Error ...
2
votes
0answers
50 views

Can I draw a histogram of the mean sample distribution (n=30) sampling from my dataset (n=200)?

I would like to test whether my data reasonably satisfies the normality assumption necessary to apply a t-test. My understanding is that, to apply a t-test, the distribution itself does not need to ...
2
votes
0answers
110 views

How to aggregate histograms for density estimation

Within a very large sensor network, each node does take measurements derived from a fixed number of samples taken at a high frequency from an instrument. The number of measurements send to an ...
2
votes
0answers
281 views

What is the correct way to modify the bin-counts given a threshold for a chi-squared test?

When performing a chi-square test, one inputs the expected counts (via integrating probability distribution over respective bin bounds) and observed counts into the chi-square formula (denoted below). ...
2
votes
1answer
649 views

How to evaluate a histogram?

Let's say I have the histogram above which reports performances of some neural networks. The y axis is the bin size, while the x axis is the error, so low errors = high performance. Out of these 15 ...
2
votes
0answers
459 views

Differential histogram bin calculation

I want to be able to minimize a difference between two distributions $P(x|\theta)$ and $Q$. I can choose Q (e.g. to be a Gaussian normal), but $P(x|\theta)$ is an unknown distribution, so I am ...
2
votes
0answers
77 views

Numerical method to compress empirical probability distribution

I am trying to grapple with the following problem. I have an application that develops empirical distributions. In essence, I end up with a histogram of equally spaced $x$ values, with both a $max$...
2
votes
0answers
25 views

IRT vs proportion/frequency

Lets say I have response data from a multiple choice exam question and I want to understand whether the item was too difficult, or if I should change it somehow to improve it What benefits do I get ...
2
votes
2answers
126 views

Displaying distributions of data with a high number of features

I have data of two different groups. From each data, I have say 100 samples, each sample having 20 features. I want to display the distribution of each of the two datasets. Now I have some very ...
2
votes
0answers
149 views

Combining histograms from different experiments

Roughly speaking (i.e., hopefully I don't need to contextualise too much), I ran an experiment five times to find the length of some aluminum sheet. Using a Bayesian model I got five different looking ...
2
votes
0answers
56 views

Low Probability Estimate from Cumulative Frequency Histogram

I've fitted a 3-parameter Weibull distribution into a sample size of $N=31392$ using Maximum Likelihood Estimation. I'm comparing exceedance probability estimates with the data's cumulative frequency ...
2
votes
0answers
47 views

Evaluation of a group of histograms

I'm trying to learn statistics on my own and currently taking an online class through edX. Unfortunately some things are not clearly explained. The online book used for this class contains the ...
2
votes
0answers
132 views

Error on histogram computed on autocorrelated time series

I am struggling to find an answer to this quite basic question. When computing a histogram on a time series which has some correlations (i.e. measurements are not independant), how to estimate the ...
2
votes
0answers
717 views

Knuth rule for number of bins of a histogram vs. chi2 fitting

I try to make a histogram and then fit some distribution to it by means of chi2. The Knuth rule (I have some bimodal cases so I'm not using Freedman-Diaconis or Scott) gives me the following histogram ...
2
votes
0answers
392 views

How to pick a good threshold for multimodal histograms

I am trying to do multi-modal detection in a vote map (histogram) however, side lobes obviously cause some false peaks. So using mean shift will not do as it will find all of the local maxima. So I ...
2
votes
0answers
502 views

On the uniform convergence of relative frequencies of events to their probabilities

I have read the article by Vapnik, Chervonenkis "On the uniform convergence of relative frequencies of events to their probabilities" Theory of Probability and Its Applications, vol XVI, n. , 1971. ...
2
votes
0answers
276 views

Establishing a dynamic threshold for partitioning data

Given a sorted set of data points, where each point represents the length of a common substring between two files, I want to systematically decide a cut off point where I can start considering them to ...
1
vote
0answers
11 views

Estimate the error bound of a histogram based mean absolute deviation approximation

Given a sequence of numbers $A = a_1, a_2, \cdots, a_n$. One way to calculate the mean absolute deviation of $A$ is by $G(A)= \sum_{i=0}^n |a_i - median(A)|$. yet, there can be an alternative, by ...
1
vote
0answers
16 views

How best to display skewed frequency data?

I am counting the number of eggs laid each day by some animals. Most days under my experimental conditions, individuals produce 0 eggs (194/307 observations). I do not want to leave these 0 days out ...
1
vote
0answers
10 views

SNR of a collection of waveforms follows the same distribution as an individual waveform

I'm generating some waveforms, produces by picking some $n$ samples from a Gaussian distribution. Not surprisingly, when I plot the sample values (i.e. a histogram with bins being the value of the ...
1
vote
1answer
82 views

Discrete data: Graphs and skewness

I am studying an introductory course in statistic " Essentials of Statistics". The author mentioned that Histograms are used to represent the frequency distribution of a contiuous data. Then ...
1
vote
0answers
18 views

Creating values from a normal inverse gaussian (NIG) distribution

I have a vector of empirical observations 'a' containing about 16000 values. empirical data The empirical histogram looks like the following: I'm trying to test, whether the normal inverse gaussian (...
1
vote
0answers
78 views

How to find margin of error for 99% confidence interval for skewed distribution?

Google Sheet of data I have the value and the frequency of the data. As you can see in the data sheet, the count number is quite high, so I am not able to write out the entire list of the data (ex. 2, ...
1
vote
0answers
92 views

Relationship between Histogram , Scatter plot , Normality , Linearity

I have the following doubt: suppose you have a categorical variable called 'neighborhood' with 20 categorical levels/values ("vila madalena", "mooca", etc). and I want to check ...
1
vote
0answers
144 views

Reference for the rule of thumb $\sqrt{n}$ for the number of bins of an histogram

Does anyone have an idea where the rule of thumb $\sqrt{n}$ for the number of bins of an histogram come from? I need a reference to put in my article. I remember that rule from my college times, but ...
1
vote
0answers
19 views

Non asymptotic error bound for$f(x)=\mathbb{E}[Y|X=x]$

I am considering the following model: $(X_i,Y_i)_{i=1}^n$ are iid random pairs with $X_i\in[0,1]$ and $Y_i\in\mathbf{R}$. Let $f(x)=\mathbb{E}[Y|X=x]$. Consider an estimate $\hat{f}_n$ of $f$. Under ...
1
vote
0answers
18 views

Visualizing historical commute times

I am looking for a visualization of travel times for a specific commute route (going from A to B, considering traffic of course), for example in a histogram. I would like to answer the question "how ...
1
vote
0answers
81 views

How to compare the chi-square distance values obtained from comparing different histogram pairs?

I have a data sequence that is generated from a computer simulation (discrete event simulation). It is a simple sequence of a single state value, e.g., 10 11 12 11 12 13 ...15. It contains N number of ...
1
vote
1answer
33 views

What is the best way of presenting many Bar Chart plots

I used R programming to produce separate 30 Bar Chart plots. The x-axis scale is the same for the 30 plots (11 bins), but y-axis is different. I want to present these results in a limited work of ...
1
vote
0answers
656 views

How to compare 2 2-D histograms and get the probability of the 2 being the same / having samples drawn from the same/very similar distributions?

I was looking at this post describing methods of comparing histograms and in particular bin-to-bin comparison and cross-bin comparison and want to know how to use these to numerically evaluate how ...
1
vote
1answer
224 views

Which regression model for percentage data with many zeros and ones?

I am analysing the share of a tree species at different forest locations. The data I am using is in percentage of the total species composition and I am modelling it based on the climatic probability ...
1
vote
1answer
186 views

downsampling a kde / combining kde and histogram

I'm calculating a KDE of one parameter (y, particle density) in bins of another parameter (x, distance from the origin). At ...
1
vote
0answers
16 views

Constructing an appropriate null hypothesis?

I have a collection of 20 2D surfaces embedded in 3D. The mean curvature of each surface has been sampled. The number of samples per surface varies from ~700,000 to ~20,000,000. The choice of ...
1
vote
0answers
65 views

Histogram of Subtraction of Underlying Values

I have histograms produced from two sets of data recording. One of background noise of values $X$ and another $Z$ with a signal of values $Y$ present such that $Z = X + Y$. How can I estimate a ...
1
vote
0answers
29 views

Why do we subtract the $cdf_{min}$ in this step of histogram equalisation?

In my question I am referring to histogram equalisation as it is described in the wikipedia article in this example here. Given an grey image $I$ of size $M \times N$, in histogram equalisation one ...