# Questions tagged [univariate]

Pertaining to a single variable. Univariate statistics deal with only one variable - e.g. the mean, standard deviation, range etc. Univariate distributions involve only one variable e.g. the univariate normal, uniform etc. distributions.

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### What is the point of univariate regression before multivariate regression?

I am currently working on a problem in which we have a small dataset and are interested in the causality effect of a treatment on the outcome. My advisor has instructed me to perform a univariate ...
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### Simple, multiple, univariate, bivariate, multivariate - terminology

I do realise (some of) this has already been addressed here (e.g., Why do we need multivariate regression (as opposed to a bunch of univariate regressions)?, Explain the difference between multiple ...
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### Imputation in a univariate time series

I am doing a univariate time series analysis on regional sea-surface temperatures which has missing data, and I am thinking about using the R package, 'imputeTS.' My model is simple, it has MA errors ...
153 views

### Graphical summaries of relationships between univariate distributions

I'd like to review published papers or book chapters (so I could formally refer to them) that graphically illustrate the parametric relationships between univariate distribution families. The papers ...
101 views

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### Random forest for forecasting univariate time series [closed]

I read few articles on random forest and its implementation in various fields. But I hardly found any literature on its implementation on forecasting univariate time series. Can it be used for ...
636 views

### Why signs of coefficients change when doing multivariate vs. univariate logit regression? [duplicate]

Excuse my dumb question, but I did an univariate logistic regression where the sign of the coefficient of my variable was negative (and it was significant). Once I have input it into a multivariate ...
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### Generates variates of $F^s$ given a known algorithm for variates of $F$

Let rv $X$ have a distribution $F (t):={\rm Prob}(X <t)$ and rv $Y$ have a distribution $G (t):=(F(t))^s$ for some constant $s>0$. Suppose that I know an algorithm for generating random variates ...
895 views

### Bootstrapping and hypothesis testing

I got a comment on a paper that I recently submitted. He said, "Pag 7: referring to the “Univariate Analysis” section, bootstrap is not mentioned. This technique is extremely useful when dealing ...
142 views

### How different will that be between the R-squared of linear regression y~x and square of cor(x,y)

Generally, both of them can represent the linear relationship between x and y scale to [0,1]. Are they 99% very similar?
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### Are the marginal distributions of a multivariate distribution the corresponding univariate distributions?

Are the marginal distributions of a multivariate distribution necessarily the corresponding univariate distributions? For example: Every marginal distribution of a multivariate normal distribution ...
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### Is multiple logistic regression the right choice or should I use univariate logistic regression?

I have a set of data (~ 90 cases) and an outcome of a diagnostic test. I have collected factors that were determined before the test that could predict the outcome of the test. Now some of the data ...
8k views

### Handling outliers in ANOVA

I have a question relative to the correct method to deal with univariate outliers when one has to conduct an ANOVA. Starting with an example, suppose I have two samples of subjects tested on a number ...
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### Chi squared test assumptions not met

I want to perform a univariate analysis to predict if a higher BMI is associated with an increased incidence of complications after surgery. I divided the BMI of patients in 4 categories (<18.5; 18....
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### Univariate cox regression hazard ratio in SPSS

I'm currently doing some analysis for a retrospective cohort study of biomarkers in cancer patients. I've noticed that some papers have utilized univariate cox regression analysis to generate a hazard ...
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### What is the best way to model such time series?

I have this time series where a peak occurs every around 5 years and the structure changes after each peak. What do you think is the best way to model such time series? Can this be modeled using the ...
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### Comparing univariate and bivariate models [closed]

I have a bivariate dataset, that is, $(\boldsymbol{y}_i, \boldsymbol{x}_i)$ for $i = 1, \ldots, n$, where $\boldsymbol{y}_i = (y_{i1}, y_{i2})$ and $\boldsymbol{x}_i = x_{i1}, \ldots, x_{ip}$ are ...
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### Definition of stable distribution

In some places, I find the following definition of stable distribution: A distribution is said to be stable if a linear combination of two independent random variables with this distribution has ...
462 views

### Univariate and multivariate outlier detection

I have a dataset with several features (about 15), and I am interested in finding outliers. My approach is to perform univariate analysis to highlight outliers in the single features and multivariate ...
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### Imputation in monthly univariate time series

I have a time series of the amount of apples sold in a specific Region. The time series include monthly values of 10 years (2006-2016). However two months are missing (February 2009 and July 2014). ...
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### Seek tool for univariate exploratory analysis

Looking for a tool to assist with univariate exploratory analysis as an early step in a model building process. Capabilities I’m looking for are to recode or transform the raw predictor variable, x, ...
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### Variable selection in time series data

I have an econometric dataset, 50 observations of 350 variables. They include things like GDP, unemployment, interest rates and their transformation such as YoY change, log transform, first ...
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### Express multivariate normal as a univariate normals

I want to find the univariate normals of a multivariate normal in order to plot them. If we assume that each are independent, then I know that we can use the mean vector and diagonal of the covariance ...
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Can we talk about univariate analysis if regression model has two dependent variables? I guess it would be incorrect. However, maybe univariate analysis means that we just analyze Y vs X1 and then Y ...
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### Estimating parameters for the product of a lognormal random variable and a uniform r.v

Suppose I have a random variable which I suspect is the product of a lognormally distributed random variable $X$ and an independent uniformly distributed variable $U(0, 1)$. (The variables are the ...
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### Different p-values for coefficients and LRT in univariate cox regression (coxph R)

I have used Cox PH to test the relationship between one predictor and survival for 6 patients. Cox PH was used since the predictor is continuous. Using the "cox.zph" function, there was no significant ...
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### 1d optimal clustering

I have the following problem - i have a range of numbers (ie. [1, 5, 7, 8, 15, 29, 100]). I need to cluster them OPTIMALLY (not local optimum as in lloyd algorithm) and better than NP time, minimizing ...
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### No significant tests when using Benjamini-Yekutieli multiple testing correction on millions of tests

I am using a univariate filter to reduce the number of features prior to applying a learning algorithm to a huge binary classification dataset (22510066 features x 500 examples). All the features are ...
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### Can univariate linear regression be used to identify useful variables for a subsequent multiple logistic regression?

Does the $R^2$ (or some other statistic) from a univariate linear regression tell me anything about how it would work in a logistic model? What if I normalized the data to mean zero? I'm doing ...
128 views

### Comparing treatment means with lots of zeros

I am trying to compare the means of two treatments on a continuous variable with a lot of zeros in it. I've tried a log(n+1) transformation but that did not get me to a normal distribution. Any ...
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### In a matched case-control study, what do I use for hypothesis testing in the descriptive statistics or the “univariate” associations?

I am doing a case-control study with 80 disease cases matched 1:3 to non-diseased controls and examining whether they had a binary exposure prior to developing the disease. I am using multivariable ...
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### Probability density function within [0,1] with specifiable mode

I needed a probability density function which worked on the interval $[0,1]$, had kind of a bell shape, and had an adjustable mode / peak $p$. I thought of a pdf $f(x|p)$, given by \begin{equation} f(...
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### Finding the parameters of bimodal and trimodal univariate distribution with MATLAB [closed]

I am rather new to Matlab and never had a lot to do with statistics, so I apologize already for possibly being ignorant of quite a bit of important knowledge. It also would be nice if you could answer ...
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### forecasting with optimised theta method (otm) using time series cross validation with R

I want to do an out-of-sample forecast experiment using the optimised theta method (otm) on a time series. Further, time series cross validation with a fixed rolling window size should be applied. ...
30 views

### Generating samples from a histogram

I don't quite know how to ask this question or what to search for but I'm certain this method has a name.. I have a uni variate binned distribution, something like x = { 0, 10 , 20 , 30,....} with ...
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### Univariate regression analysis - unexpected sign

I am performing an univariate regression analysis by basically regressing a default rate on macro economic variables such as $DR = \alpha + \beta GDP$ I noticed that sometimes the sign of the betas ...
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### In univariate logistic regression, does the scale of values affect the predicted “risk” at a particular value of the independent variable?

I have many datasets representing different populations. Each dataset contains values of an independent variable along with (0/1) representing the occurrence of an undesirable event. I analysed each ...
523 views

### expressing a univariate normal as a multivariate normal

I need to express a univariate normal as a multivariate normal to make certain calculations possible (for example: being able to divide two Gaussian distributions). So, my univariate normal is defined ...