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Questions tagged [bimodal]

A bimodal distribution is a probability distribution with two different modes. These appear as distinct peaks (local maxima) in the probability density function for continuous distributions and the probability mass function for discrete distributions..

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How to calculate the moments and median of a bimodal distribution by sampling? [duplicate]

This question is from the book An Introduction to Generalized Linear Models The bimodal distribution is the sum of 2 normal distributions $N(2, 1)$ and $N(5, 0.5^2)$. I thought the sum of 2 normal ...
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What model would be best to analyze bimodal distribution?

I have some data that is causing a bit of a pickle. We ran a dietary experiment on 500 invertebrates for 4 weeks; 250 invertebrates were given a Phosphorus-enriched diet and the other 250 were given a ...
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Linear mixed model predictor distribution not fitting any of the options

I am looking at the effect of beaver dams on water levels. Can I use the lme4 R package with a generalised or linear mixed model, and how? My data doesn't seem to ...
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Can bimodality exist in a multivariate sense?

Consider a hypothetical discussion about a Lotka–Volterra experiment involving foxes and rabbits: ...
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Find maximum of bimodal posterior pdf

can you help find the maximum (analytically) of the following posterior pdf? $p(\theta|x) = \frac{\alpha}{\sqrt{2\pi}}e^{-\frac{1}{2}(\theta-x)^2} + \frac{1-\alpha}{\sqrt{2\pi}}e^{-\frac{1}{2}(\theta+...
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How do I interpret this plot?

I'm finding it hard to interpret this plot. Is it skewed, bimodal, or what is it? What do the points lying in the same line and rising suddenly mean? Is it exponential?
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Statistical Test for showing variance in peak values of two different populations?

I am publishing a paper and one of the reviewers requested that I provide a statistical method to show the difference between peak values (peak value = tallest bin in a histogram) of two populations. ...
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Bimodal distributions & hypothesis testing

TL;DR: How to evaluate effect of variable on (bimodal) outcome? Context Please see below a faceted histogram of the outcome variable (Total Absolute Score) of a recent experimental (psych) study. The ...
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bimodal outcome - non normally distributed residuals

I have an outcome variable that is bimodal, this is because in about half the sample is measured from 0 to 5, and half the time from 0 to 7. Because of the different scales, I have decided to ...
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What test to implement for a regression where points are biomdally distrbuted (i.e. two peaks)?

The data looks at abundance vs rainfall. Abundance peaks at low or high rainfall. Fitting a quadratic creates a false peak at intermediate rainfall. What's the best type of regression to fit here? ...
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Standard deviation on Bimodal data

Standard deviation, whilst it is often used on normal distributions, is it a useful statistic on global temperature, both daily and yearly, given that weight of the data is towards the ends of the ...
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Statistics to use on Bimodal data

What summary statistics, mean, median, standard deviation, etc. should be used on a skewed, bimodal, dataset and why? These are almost U shaped in a histogram layout with a slight preference for lower ...
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If we numerically code the categories of an ordinal variable, then can we determine its mean as in Likert scale?

Can anyone clear my doubts about 2 things. Doubt1)A dataset of Ordinal type having 2 modes, then does it mean that such dataset have 2 central locations ? Doubt2)As We know that we can not determine ...
hornet's user avatar
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Regression on bimodal target variable

I'm working on a problem where I need to fit a regression on solubility data from a collection of molecules. The response variable (solubility) displays a bimodal distribution, suggesting there are ...
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Compute a quantile of a bimodal distribution composed of two normal distributions with known parameters [duplicate]

I have a bimodal distribution which is an equally weighted mixture of two normal distributions with known means and standard deviations. I can easily compute a two quantile values using the percent ...
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Mode for equal consecutive frequencies

I'd like to calculate the mode for the frequency distribution table: ...
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Recovering Bimodal distribution parameters using pymc3

I am trying to determine the parameters mu1, mu2, sigma1, sigma2, and w of a bimodal distribution using pymc3. x ~ w * Norm(u1, sigma1) + (1-w) * Norm(u1, sigma2) I use the following code: ...
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How is a Bimodal distribution platykurtic?

I am trying to understand how the distribution on the right is platykurtic? I learned that platykurtic indicates lighter and thinner tails and from what it looks like, the bimodal distribution, with a ...
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Statistic for measuring the magnitude of bimodality in a distribution?

Here are some distributions of US political views by industry: After observing their mostly bimodal nature, I would like to measure the degree of bimodality in each of the distributions for the ...
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Difficulty splitting bimodal data

I'm working with a bimodal data set and need to split this bimodal data to 1) estimate the proportion of data points in each distribution and 2) the mean of each distribution. I have approached this a ...
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Sum of Bimodal Distributions? [closed]

If I'm trying to estimate a the sum of a bunch of random variables, where each random variable is a bimodal distribution, how would i go about thinking or modeling what that looks like?
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What is a reasonable method for two sample test on cut-off measurements?

This is a question regarding biostatistics. I am digging into some statistical analysis with SingleCellSignalR, which is a tool to predict cellular interaction with single-cell RNA-seq data. I was ...
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What distribution does this data take?

I have several unique ID's that have this distribution, but I cannot find any information on the type. I'm leaning on this being a bimodal distribution, but am not sure. I need to fit these to a ...
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Can I do a hypothesis test to see if two populations are different if there are known subpopulations within the data?

I have a continuously variable output (diffusivities) that I have measured from two different populations (say "Case 1" and "Case 2"), and I am trying to see if the two populations ...
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How to apply a statistical test on either a bi-modal distribution OR how to transform it to parametric?

I have lifetimevalue (LTV) data for 3 groups in my set. For each group, their respective LTV looks bi-modal. I need to test if there is a statistical significance between those groups with respect to ...
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Normalizing a strongly bimodal distribution

I am working with measurements of "spring vigor" of a perennial plant measured on a 0-20 scale. It is meant to screen for winter damage. In this experiment, there are many individuals who are ...
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1 answer
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difference between binormal and bimodal?

I am trying to simulate in R a normal distribution with two different means, and I wrote: ...
Chicago1988's user avatar
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802 views

Data transformation : bimodal feature

I have a data feature that follows closely a bimodal distribution (mixture of two separate normal distributions with different mean, standard deviation and weights). Is it meaningful to transform that ...
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testing whether data comes from a bi-modal distribution (python) [duplicate]

I have a variable which seems to be a mix of two Gaussian distributions (it is bi-modal with each mode looking normally distributed). I would like to identify anomalous samples. So my idea is to ...
Nick's user avatar
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Comparing 2 mixture models using mixtools

I have 2 mixture models I'd like to compare. Specifically, I want to compare lamda (i.e. proportion/area under each distribution) as it looks like there are differences there. Is this possible? ...
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Splitting of bimodal distribution, use in regression models

I have a bimodal length-frequency distribution for the females of a species with a one-year life span. This pattern is not observed in the males. I suspect that the bimodality is due to different ...
watermineporcupine's user avatar
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Can we model a bimodal response variable using a mixed effect model?

I have a response variable that is bimodal (basically, 2 normal distributions that are sticked together) and want to model it using a linear mixed effect model. Here is a quick example (in R): <...
M. Beausoleil's user avatar
1 vote
1 answer
683 views

Is it appropriate to use the mean of the distinct u̶n̶i̶q̶u̶e̶ values from a bimodal distribution to split the data?

I have sets of data with a bimodal distribution and the best estimate of splitting the two seems to use the single (unique) values that can be taken, and calculate the mean. This mean value nicely ...
Geo Vogler's user avatar
32 votes
3 answers
8k views

Why is a mixture of two normally distributed variables only bimodal if their means differ by at least two times the common standard deviation?

Under mixture of two normal distributions: https://en.wikipedia.org/wiki/Multimodal_distribution#Mixture_of_two_normal_distributions "A mixture of two normal distributions has five parameters to ...
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How to find groups inside the dataset (test for bi-multimodality)

I have non-normally distributed dataset, a record of a parameter, e. g. 50 subjects reacted to stimulation, (9 periods of time in total). So I have a matrix of 50x9 numbers, 9 medians for each time-...
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How to sample/fit distribution from/for bi-modal data [closed]

The context is: I have a sequence of data, of which the histograms show a bi-modal pattern. My final goal is to sample from this sequence in a simulation project. Now we want to fit a parametric model ...
Undecided's user avatar
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2 answers
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Causes of bimodal distributions when bootstrapping a meta-analysis model

I help a colleague to bootstrap a meta-analysis mixed-effects model using the metafor R package framework authored by @Wolfgang. Interestingly and worryingly, for one of the model's coefficients I ...
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Theoretical reason for 1 linear model not being able to model a bimodal distribution?

Recently, I got a set of data where I try to predict the label (a continuous variable between 1000 - 3500) given 13 feature variables. By applying the kernel density approximation on the label (shown ...
Rui Nian's user avatar
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2 votes
2 answers
664 views

How to engineer a bimodal continuous feature for use in Decision Tree?

I have a predictor that exhibits "bimodal" behaviour. How can I engineer this feature to improve performance within a Decision Tree? For an intuitive example, consider how a binary flag of "moves ...
Ben's user avatar
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How do I Identify a cutoff value from bimodal data?

I am putting together a regression model with data of carseat sales from the ISLR dataset. It is sales as a function of the independent variables. One of the variables has a bimodal distribution I ...
Sebastian's user avatar
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3 votes
1 answer
10k views

How do I normalize a bimodal distribution?

I'm working with the Iris dataset. One of the variables, PetalWidth, has a clear bimodal distribution. My understanding is that multivariate regression sssumes ...
Sebastian's user avatar
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0 votes
1 answer
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Can I perform KMeans on a bimodal data?

I am preparing a dataset for KMean clusters. But a series of data appears to be bimodal: My question is: Can I perform KMeans on a bimodal data? If not, what kind ...
Cheng's user avatar
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1 vote
1 answer
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Testing for difference in means with bimodally distributed data?

I have two bimodal distributions of data with two peaks (one around 0 and the other around 1). I have provided an example of one of the distributions. Although their means and variances are different,...
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Dependent variable - bimodal?

I have a dependent variable, days.to.event, that looks almost bimodal at 0 and 30. I understand that there is no transformation that can normalize this. In fact, when I fit a linear model (lm) with ...
SanMelkote's user avatar
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125 views

One dataset, two populations?

Setting: I have a single dataset from a simulation that appears to demonstrate bimodality. The dataset is composed of N measurements calculated at n different times and is two dimensional (N by n). At ...
Alex's user avatar
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9 votes
2 answers
10k views

Simulating a bimodal distribution in the range of [1;5] in R

I want to simulate a continuous data set/variable with lower/upper bounds of [1;5], while at the same time ensure that the drawn distribution can be considered as bimodal. Searching for my problem, I ...
deschen's user avatar
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2 votes
2 answers
2k views

Choosing center of histogram bins for fitting

I have a bimodal distribution, and if plotted with Mathematica it looks like this: Now, the lowest value from the actual data is 8196 and 690720, but as seen in the plot, Mathematica lets the data ...
user avatar
2 votes
0 answers
53 views

Multimodality of mixtures of more than two Normal distributions

Let $$\phi(x;\mu,\sigma) = \frac{1}{\sigma \sqrt{2\pi}} \exp \left(- \frac{(x-\mu)^2}{2\sigma^2}\right)$$ denote the Gaussian density function ($\sigma > 0$). Let $$f(x) = \sum_{i=1}^N p_i \...
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Bimodal distribution dispersion

what is the correct way to study the variability of a data set when all the observations are distributed like a bimodal distribution? For instance, here I identified the two modes as central index. ...
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Is this distribution bimodal? [duplicate]

so understanding what unimodal, bimodal & multimodal distributions mean was easy, but I wonder how strict should I be when I am applying the definitions to real data, in that sense, I need to ask, ...
Ammar Aldawoodyeh's user avatar