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
0answers
22 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 ...
0
votes
0answers
34 views

Time series Exponential smoothing by Holt winters method

I have basic questions with respect to exponential smoothing techniques, from statsmodels.tsa.holtwinters import ExponentialSmoothing add_model = ExponentialSmoothing(traindata,seasonal_periods=12 ,...
1
vote
1answer
38 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 ...
0
votes
2answers
22 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 ...
2
votes
1answer
78 views

Claims and questions regarding $n$-ball distribution?

CONTEXT In my research, I am utilizing an $n$-sphere 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 ...
0
votes
1answer
63 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. ...
1
vote
0answers
31 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 ...
4
votes
1answer
55 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 ...
0
votes
0answers
38 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 ...
1
vote
2answers
30 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 ...
0
votes
1answer
28 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 ...
0
votes
0answers
25 views

zero-lag filter: size of negative part of filter weights: when in-phase with sinusoid?

This question is about negative weights in causal filters and their effect on the lag, or "synchronization" with a sinusoidal signal. There are a few types of moving averages that use negative ...
5
votes
1answer
149 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 ...
1
vote
1answer
350 views

Univariate ANOVA: how to deal with independent variables that are subsets (SPSS)?

I have speech recordings which have been assigned opinion scores (1-5). These recordings were performed by 10 speakers, 5 male and 5 female. I want to investigate the influence of both the specific ...
0
votes
1answer
86 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 ...
5
votes
0answers
99 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;~\...
0
votes
0answers
27 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 ...
0
votes
0answers
29 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 ...
2
votes
0answers
52 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 ...
2
votes
2answers
114 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?
1
vote
0answers
20 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 ...
0
votes
1answer
50 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 ...
0
votes
0answers
9 views

Appropriate analysis for univariate proportion data and environmental variables

I'm new to statistics so am trying to choose the best analysis to find if; There is a difference between canopy cover (0-100%) at different sites There is a relationship between canopy cover and ...
0
votes
0answers
24 views

Generalized logistic distribution

I saw on wikipedia https://en.wikipedia.org/wiki/Generalized_logistic_distribution that when $\alpha<\beta$, generalized type IV logistic distribution can be written as: $\frac{\exp(-\alpha x)}{(\...
0
votes
2answers
45 views

Which test you recommend?

Assume in a study the dependent variable is quantitative, while most independent variables are categorical, with some of them being quantitative. We aim to evaluate the relationship between the ...
0
votes
1answer
31 views

what is alternative/opposite to piecemeal statistical approach?

I have only basic knowledge about bio-statistics. For not normally distributed data, I used Kruskal-Wallis test to investigate the statistical significance between different variables. I performed an ...
0
votes
1answer
18 views

Which command should be used in SPSS for calculating p value without confounding factors effect?

In a study, we have the disease as dependent variable ( 0 or 1 patient or healthy); some independent variables are real and some of them are confounding (some of varibles are quantitative and some of ...
0
votes
2answers
546 views

p-value for univariate analysis

So I am reading an article in which it has a table showing p-values and hazard ratios for what they say is "Univariate and multivariate analyses of clinical and treatment factors potentially ...
0
votes
0answers
18 views

Univariate time series for multiple devices

I have about 50k devices, which either fail (0) or connect (1). I have data for the past 300 days for all of them. I'm trying to predict when a device will next fail. The devices are all more or less ...
13
votes
4answers
518 views

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 ...
0
votes
0answers
53 views

Univariate Feature Selection KBest Test Score Function with Binary Target

What is/are good score functions for univariate feature selection tests when the target variable is binary? Are any of the available scoring functions bad, aside for the regression functions of course....
0
votes
0answers
53 views

multi-response outcome: multivariate or univariate regression?

I have a dependent variable which represents participants' responses on 20 words, coded as 1 = correct , 0 = incorrect Question: I am keeping the regression as univariate for now (as far as dependent ...
0
votes
1answer
48 views

Concept of square in multivariate statistics

This might be more of a linear algebra question, but here we go. I have always been confused about how the concept of squares in $\mathbb{R}^1$ sometimes corresponds to a matrix product $A^{T}A$ and ...
0
votes
1answer
85 views

How can I implement univariate Nadaraya-Watson regression for prediction?

How can I implement univariate Nadaraya-Watson regression for prediction? And what is the $x ,x_i$, and $y_i$? How can I select the $x ,x_i$, and $y_i$? The sample for prediction and the shape of ...
1
vote
1answer
553 views

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 ...
1
vote
0answers
31 views

Which statistical test to use in R? Unbalanced design with one dependent variable and multiple independent variables

it's been a while since I've had to do any statistics and I need a little help determining which statistical model/test to use in R. My background is more with multivariate stats, so it's been a while ...
1
vote
0answers
292 views

Filter methods for feature selection are often univariate. What multivariate filter methods exist, and what are their dis/advantages?

Feature selection approaches are often grouped into three categories: "filter", "wrapper" and "embedded" approaches. Filter methods tend to assess the inclusion of an attribute based on some scoring ...
1
vote
1answer
72 views

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 ...
2
votes
0answers
28 views

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 ...
0
votes
0answers
192 views

Box-Cox Transformation on Single Variable and Interpretation of the Transformed Variable's Mean and Standard Deviation

I'm revisiting the Box-Cox transformation in one of my stats books, and I started playing around with the SAS macro %BCTRANS2 (Source: http://support.sas.com/resources/papers/proceedings12/430-2012....
0
votes
1answer
48 views

Can we use a univariate regression as a dimensionality reduction method?

Assume we have 500 predictors and one response. Can we perform a univariate regression on each pair Y-X and then select the predictors that have the highest R-squared and p<0.05? After that, we can ...
1
vote
0answers
87 views

Interpreting results of mvnorm.etest using energy package in R

I need to use functionalities of the energy package installed in R to give energy test of normality. So, as given in its documentation here https://cran.r-project....
0
votes
2answers
466 views

Derive Spearman correlation (rather than Pearson's) coefficient from a univariate regression?

In univariate regression, the standardized coefficient is equal to the Pearson correlation coefficient. When the two variables are ranked variables, Spearman correlation would be appropriate. Is it ...
3
votes
1answer
411 views

How to adjust for a temporary 12-month level shift in time series?

I am working with a time series on monthly base (April 2004 - Oct 2016) in order to identify an ARIMA model and do forecasting. This is the time series I examine: month;volume Apr 04;2.555 Mai 04;2....
2
votes
0answers
428 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 ...
1
vote
0answers
9 views

Index creation for studying “average” time series properties

I have 300+ financial time series from an "unknown" asset class. To study the dynamic properties of class my idea was to collect them under an "index" and then study it as an univariate time series. ...
1
vote
2answers
580 views

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 ...
0
votes
0answers
56 views

What is a qq plot? Is it possible to make a qq plot between age (ranging from 20 to 70) and salary (ranging from 5000 to 10000)?

What I have understood is that it is a graphical technique used to check if 2 data sources (even if not from the same population) have similar data distribution. In that case the scatter plot will be ...
1
vote
0answers
44 views

Is it mathematically correct to re-analyse data as ordinal after having analysed as continuous using the same rank based method (nparLD)?

Please tell me why I'm wrong :) I have a dataset collected in a 2 by 4 repeated measures design, where 2 separate groups of people were tested 4 times on the same task. I have analysed my data with ...
1
vote
0answers
58 views

Statistical significance vs.classification accuracy

Apologies if this question has been asked before, but I could not find very relevant topics. I am working with proteomic data (40 proteins, 800 instances) where the outcome variable is binary (...