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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Determine if a series of discrete distributions are expected

*I apologize for the length of this post and I have almost no statistics experience, please keep that in mind :) In competitive diving, a diver will perform 5 different dives and will receive scores ...
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Build a model with bimodal output

Let's say that you want to build a model that predicts two possible outcomes with a probability for each. To be clear, i'm not talking about a problem where the target variable is binary and you want ...
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Quantification of “modality” of distribution

Does anyone know of a quantification of the modality of a distribution? For example, exactly how "high" must the "second" peak be in order to qualify as bimodal rather than unimodal with some un-...
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Test for differences in distributions; three samples; multimodal distributions

Here is a question on how to test for differences in distribution between three samples of multimodal distributed data. I have conducted a dictator game (http://en.wikipedia.org/wiki/Dictator_game) ...
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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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How to statistically distinguish between two types of time series (bimodal vs. not bimodal)?

I have two different types of time series. The first group of series is much more bimodal, and the second group is much flatter. For a given time series, I want to test whether it more likely belongs ...
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Observing seasonality in a time series

I've got a time series which plots surface reflectance over time. Ideally surface reflectance is high in the winter and is low in the summer, and is fairly constant during both of those periods. I ...
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701 views

fitting mixture of bimodal distribution

I am trying to fit my data with a bimodal distribution using two beta distributions, however it seems to me that the two peaks are not captured very well. The reason that I notice from the data is ...
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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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27 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 ...
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188 views

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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315 views

Bimodal posterior distribution

Do you know in which situations is it possible to have a bimodal posterior distribution for some parameters? I couldn't find any information on the web. Thanks for your help.
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Modes and antimodes in apparent trimodal distribution with R

Suppose I have the following white blood cell counts: ...
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Geometric mean appropriateness with bimodally distributed data

I am trying to find out whether the performance of the geometric mean of a distribution as a measure of its central tendency would be impaired by the distribution being multimodal. For example, ...
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variance of a mixture in terms of the mean and variance of each component

I am following the MATLAB example to fit a mixture of two normal distribution that you can find here At some point it is defined the inital guess for the standard deviation as: ...
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374 views

How to deal with multi-modal distributions in hypothesis testing?

Say that I collected random variable X from one population and a random variable Y from another population. I want to apply a statistical test to determine whether these two populations are different....
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PCA on bimodal data: how to standardize the data?

My set of data points can roughly be broken up into 2 sets with different means. In each set, the points are close to each other (geometrically). Moreover, the variance is the same across both sets of ...
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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): <...
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Data set for mixed distribution - bimodel

I'm doing my undergraduate thesis and I need to have a data set which is distributed as bi-model in order to complete the application part. I'm going to use non- parametric methods to estimate the ...
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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 ...
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Bi-modal coefficient estimates of bootstrapped difference in differences estimate

I'm trying to conduct a sanity check on a really strange result I'm finding. I specified the following difference in differences logistic model in R: $Pass = \beta_{0} + \beta_{1}Attended\times\...
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Shared latent spaces

I have two interrelated response variables $A$ and $B$ over each observation $i$ in my data. I am trying to create an unsupervised model where observations could be explained by means of latent spaces(...
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How does the presence of multimodally distributed variable/ parameter effect my model?

I have come across this sentence many times - "All xs should come from same distribution'. I wanted to understand how will the presence of a multimodally distributed variable effect my modal. I have ...
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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 ...
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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 ...
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Simulate a 2D-beta distribution: spatial simulations

I'm doing spatial simulations and I would like to simulate a matrix that represent a truncated 2D-bimodal distribution with U shape. In other words, I would expect high density towards the borders of ...
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471 views

Is there such thing as a discrete bimodal distribution, and how do I go about hypothesising a distribution for my data?

I've got discrete data (highest education level achieved to be exact, where each level has an associated integer, from 1 to 7, with a higher number corresponding to a higher education level). The two ...
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353 views

What is the best approach to transform independent variables that have a bimodal relationship with the dependent variable?

I am building a logistic regression model with a binary rating (High and Low) as the dependent variable and 40+ independent variables. One of the independent variable (Age) has a non-linear ...
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Estimating multimodal (1-3 modes) signals

I am trying to estimate measured signal, which has multimodal behaviour, usually 1-3 modes (see trimodal sample frequencies below for example), but in one experimental setup it's 1, 2 or 3 all the ...
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Testing for difference in bimodality between experimental groups

I conducted an experiment with three treatments (A, B, control), measuring for each subject a response variable that varies between 0 and 1 (a continuous proportion). The resulting distributions of ...