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.

Filter by
Sorted by
Tagged with
0 votes
0 answers
33 views

Univariate after stepwise regression?

My aim is to understand and describe the effect that independent variables (ordered and unordered factors and continuous) have on a continuous dependent variable. First, I thought about using a ...
user avatar
  • 1
0 votes
0 answers
29 views

Joint density and univariate time series models

Is the picture below an example of univariate time series model since I am observing the same random variable just at different time points? Can joint density be used to explain univariate time series ...
user avatar
  • 1
1 vote
0 answers
23 views

Under what conditions does univariate variable prescreening fail? (random forest modeling)

Univariate statistical methods are often used to prescreen variables for possible inclusion in a model. For example, running random forests (RF) with only a single predictor at a time to prescreen ...
user avatar
  • 273
0 votes
0 answers
25 views

Survival analysis - univariable and multivariable regression [duplicate]

I am running an analysis of various factors that determine whether an individual is likely to have an event. My outcome is binary (0 vs 1), and my explicative variables can be both quantitative or ...
user avatar
  • 165
1 vote
0 answers
16 views

What methods to do for analysis

So i am designing a study where there are 2 groups of students. One group which is part of Y number of departments have not received trainingA. The other group of students which are part of X number ...
user avatar
  • 371
0 votes
0 answers
40 views

how to quantify the strength of trend in univariate time series data?

I have data that looks something like this: ...
user avatar
0 votes
0 answers
47 views

How to handle missing data in the univariate analysis

Can someone please advise me on how to handle missing data in the univariate analysis (e.g. t-test, chi-squared test)? Given that the multiple imputation techniques (MICE package) are for multivariate ...
user avatar
1 vote
0 answers
24 views

How does aggregation across time bring about feedback?

On page 11 Pankratz says: "Sometimes there is sound theoretical reasoning in favor of a one-way relationship from the inputs to the output (no feedback). But even then it is important to have a ...
user avatar
0 votes
0 answers
22 views

How to accommodate for covid-19 shocks in SARIMA when forecasting economic variables?

I am trying to forecast an economic variable using 1.Univariate Model 2.Multivariate Models Due to covid-19, there is a huge drop in the considered variable and it impacts the accuracy. However the ...
user avatar
  • 109
3 votes
2 answers
188 views

Regression not significant on univariate but significant when adding controls

I have a data on job type (i.e. dummy variable 1 if bad job and 0 if good job) and amount of debt individuals hold before finding a job. I ran a regression of job type on debt level, and I did not get ...
user avatar
8 votes
1 answer
183 views

Can a (possibly infinite) mixture of Gaussians be Gaussian?

Suppose we define a (possibly infinite) mixture of zero-mean Gaussians: $$p(x) = \int_{\mathbb{R}^+} N(x; 0, \sigma^2)\ \pi(\sigma)\,\text d\sigma,$$ where $\pi$ defines the mixture components. ...
user avatar
  • 81
0 votes
1 answer
48 views

How to establish a standardized score for non-normal/long-tail distribution

Apologies if this is an elementary question. My rusty high school understanding of statistics has left me a bit lost to the following problem. Essentially, I have several long-tail distributions of ...
user avatar
1 vote
1 answer
67 views

Is this an example of a univariate analysis?

Nonstatistician needs help with terms. Is the following an example of a univariate analysis?: Chances of getting a job at Microsoft with respect to demographic variables such as age, gender, race, etc....
user avatar
  • 111
2 votes
1 answer
925 views

Rolling vs Recursive vs Fixed Window Regression

What precisely are the differences between rolling, recursive and fixed window regression? As far as I understand, recursive: we train on a period $y(0)$ to $y(n)$ then predict $\hat{y}(n+1)$. Then ...
user avatar
  • 203
0 votes
1 answer
39 views

Covariance of $x_i$ and $\hat{\varepsilon}$ without exogeneity of $\varepsilon$

What is the $Cov(x_i,\hat{\varepsilon})$ if $E(\varepsilon_i|x_i)\neq0$ in a univariate regression model? Can the expression be simplified further beyond $\sum(\hat{\varepsilon}_i-\bar{\hat{\...
user avatar
  • 1
0 votes
1 answer
18 views

Find treshold to separate two classes based on single predictor

I have a binary output variable (not healthy, healthy) that I want to classify. I found based on univariate analysis that one of my independent predictors already tells apart both classes perfectly. ...
user avatar
  • 164
0 votes
0 answers
173 views

How do I treat zero inflated univariate time series data?

The data I am handling is a rainfall data. The only columns are "Date" and "Rainfall". The day that is not raining will be accounted to zero, therefore it is a zero inflated ...
user avatar
  • 3
3 votes
2 answers
1k views

Univariate or Multivariate Time Series?

I believe univariate time series pertain to one single variable changing over time and multivariate refer to multiple variables (either dependant or independent), however the following case is unclear ...
user avatar
1 vote
1 answer
326 views

How to choose variables for multivariable cox regression analysis based on univariable analysis results?

I want to conduct a multivariable cox regression model to assess predictors of "Mortality" variable. Assume there are three independent variable as follows: Gender --> (dichotomous= 1,2) ...
user avatar
  • 197
0 votes
1 answer
94 views

Copula between a distribution and its univariate transformation

I'm trying to compute the copula (or joint distribution) between x and a univariate transformation, like say sin(x). That is compute $C_{XY}$ (or $F_{XY}$) given that $x \sim U(0,1)$ and $y = sin(x)$ ...
user avatar
  • 41
0 votes
3 answers
77 views

Selection of variables based on clinical knowledge in multiple logistic regression

Dear Cross Validated community, I am conducting a multiple logistic regression for a case-control study. There are too many predictors to be investigated. My question is "Can I choose which ...
user avatar
0 votes
0 answers
17 views

How to represent dependencies between horizons and uncertainty when forecasting multiple horizons?

Suppose the following case of univariate time series forecasting. We forecast sales of a product 1 till 7 days ahead. The true distribution of the actual sales is the following: there is a 100% chance ...
user avatar
  • 113
2 votes
1 answer
354 views

Question regarding selection variables for a multiple logistic regression analysis, through univariate analysis

I use univariate analysis to select variables for a multiple logistic regression. However, one of the categorical independent variables has a non significant dummy (one of the three). Should I include ...
user avatar
  • 21
7 votes
1 answer
206 views

Does this distribution have a name? $p(x) \propto |x|^a \exp\left(-\frac{1}{2} (x-b)^2 \right)$

Quick question. Anyone able to attribute the following kernel to a known probability distribution (univariate, continous on the real line)? $$ p(x) \propto |x|^a \exp\left(-\frac{1}{2} (x-b)^2 \...
user avatar
  • 81
1 vote
1 answer
106 views

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. ...
user avatar
  • 15
1 vote
0 answers
45 views

No significance in the multivariate tests

Hope this question is not too stupid. I haven't taken the MANOVA course yet, but I need to figure out a problem right now. I am running a mix-model MANCOVA on SPSS. I have no significance in the ...
user avatar
  • 11
1 vote
1 answer
135 views

Univariate Competing Risk Analysis with R

I need to carry out a competing risk analysis, and I am using this paper as a guide. The first question: the exp(coef) is the hazard ratio? The second: how could I carry a univariate analysis (I need ...
user avatar
  • 11
1 vote
1 answer
336 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 ...
user avatar
  • 25
2 votes
1 answer
66 views

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....
user avatar
  • 41
2 votes
1 answer
47 views

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 ...
user avatar
0 votes
1 answer
125 views

Statistical analysis of amino acid profiles, quantitative vs qualitative methods?

I work on a study comparing the amino acid profile of 5 sample groups with 3 replicates in each group. This is how the data looks like except that there are 17 columns (one for each amino acid) in ...
user avatar
  • 65
4 votes
1 answer
8k views

How to set (p,d,q) and (P,D,Q) for SARIMA time series model

I have a time series dataset of monthly average temperature in Cayman from year 1823 to 2013, with dickey-fuller test = 0.008275 (I assume the series to be stationary since the test doesn't exceed 0....
user avatar
  • 41
0 votes
0 answers
96 views

The utter futility of bivariate analysis

Consider the following quote from here: Moreover, univariable prefiltering, sometimes also referred to as “bivariable analysis,” does not add stability to the selection process as it is based ...
user avatar
  • 133
1 vote
1 answer
135 views

Uni-variate hourly time series anomaly detection by TBATS

I have hourly and +4 years length of air pollution data (PM10). It has 24 (daily), 168 (weekly) and 8766 (yearly) seasonality. Also distribution is right skewed and has very long tail. I want to make ...
user avatar
  • 131
0 votes
2 answers
57 views

The sufficiency of univariate selection

Why is feature selection such a common topic, when one could simply use SelectKBest to find the optimal set of features? The only trouble would be to find the best ...
user avatar
  • 133
1 vote
1 answer
5k views

How to plot cost function against iterations? [closed]

I am new to coding in machine learning. I am trying to plot a graph for the gradient descent of a univariate function. ...
user avatar
1 vote
0 answers
453 views

Univariate vs multivariate analysis (p-value)

So I have been looking through some literature/articles, and something I often come across is, that when they do some kind of analysis it's often univariate and multivariate analysis on for example ...
user avatar
4 votes
1 answer
617 views

In a linear regression hypothesis equation, what does each symbol represent?

So I've been watching Andrew Ng's machine learning lectures, and I'm on a video about univariate linear regression. He was talking about how a Hypothesis takes an input and predicts an output, like a ...
user avatar
  • 155
1 vote
2 answers
195 views

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 ...
user avatar
  • 589
1 vote
1 answer
689 views

LSTM model for multistep univariate Time series forecasting

I have scenario where i have time series data (1 per day) for past 365 days. And I need to make a prediction for next 365 days. Is this possible using LSTM or any other ML models. I have been through ...
user avatar
  • 13
0 votes
1 answer
119 views

Logistic regression interpretation in SPSS statistics

I observed a very strange behavior while doing logistic regression, univariance analysis and correlation analysis. I have dependent binary variable and several independent variables that should be ...
user avatar
3 votes
1 answer
480 views

Claims and questions regarding $n$-ball distribution?

CONTEXT In my research, I am utilizing an $n$-ball distributions along with two related distributions. I'd like to make certain I have a firm handle on the way to describe my three distributions. I ...
user avatar
0 votes
1 answer
2k views

Is the chi square test one type of univariate analysis?

Somewhere I read that for categorical variables, the univariate analysis includes only descriptive information. What about chi square test? Could not we assume the chi square test as univariate ...
user avatar
5 votes
0 answers
107 views

Is there a standard name for this continuous distribution? [closed]

I'm encountering the following PDF of continuous scalar real $X$ with semi-infinite support $]0,+\infty[$: $$ f_X(x) = C ~ x^{-\alpha} ~_1F_1\left ( a,b;-\frac{d}{x^\beta} \right ),~~~~~~\beta>0;~\...
user avatar
  • 121
0 votes
0 answers
66 views

Correlation between univariate time series

I'm wondering about what preprocessing steps are common before taking correlation between univariate time series. I usually normalize the data, but I'm also wondering if the spacing is important as ...
user avatar
0 votes
0 answers
32 views

Is it possible to do forecasts using regression algorithms and only 2 variables?

I have a dataset with 2 variables: "_time" and "logins". I trained a model with the month of MAY. Then I applied that saved model on the month of JUNE (this is unseen). Is it possible to use a ...
user avatar
  • 1,019
2 votes
0 answers
62 views

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 ...
user avatar
2 votes
2 answers
210 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?
user avatar
  • 135
1 vote
0 answers
48 views

Creating multivariate regression model out of multiple univariate models

A bunch of ML regression models are defined only for predicting the value of a single variable. Or have standard implementation that are only for the univariate case. For example support vector ...
user avatar
0 votes
1 answer
65 views

Verifying Identification Results for Univariate Regression

So I have this linear regression model shown below and I'm supposed to be showing that equation 3 is equal to equation 4. There's a hint that says a 2x2 inverse matrix appears in the proof, but the ...
user avatar