Questions tagged [continuous-data]

A random variable $X$ is called continuous if its set of possible values is uncountable, and the chance that it takes any particular value is zero ($\text{P}(X = x) = 0$ for every real number $x$). A random variable is continuous if and only if its cumulative probability distribution function is a continuous function.

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How to decide whether to use regression or classification model?

I just started machine learning , and I was confused about which model to use, regression or classification , when we have a target variable like age or a variable like movie rating , which may have ...
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Latent Profile Analysis in R with continuous and categorical variables

I am trying to do an LPA with categorical and continuous variables. The tidyLPA package is amazing for continuous variables but models don't seem to converge with categorical variables, and the ...
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21 views

Represent Integer Categorical feature as both Numeric and Categorical

I'm dealing with tabular datasets where it's really hard to tell if the integer column is Numeric or Categorical. My main consideration is the accuracy of the model that I am building (no deep ...
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Linear regression or something else? [duplicate]

Premise: I know there are lot of questions like this one. The reason why I'm posting it anyway it's because I'm not sure about the real nature of one of my two variables. I want to determine if two ...
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Analysis of One Binary Variable and Continuous Variables - Ecological Data

I have a dataset that I am trying to analyse, it consists of: A binary variable which indicates a tree species (0 = deciduous 1 = evergreen) with 100 measurements each. N which is leaf nitrogen ...
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57 views

How to compute the median of a continuous distribution?

I don't have a solid background in statistics so the concept of probability density functions in the statistics course I'm taking is new to me. I need to derive the median of a continuous distribution ...
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In practice, how to discretize continuous regressor with minimal impact on coefficient (or minimal information loss)?

Suppose I have some continuous data that looks like this (this is a mini example, not my real data): ...
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Are zero inflated models appropriate if the predictor/x variable is the one that is zero-inflated?

As the title suggests. I was under the impression that zero-inflated models are generally used when zero values are over-represented among the response/y variables, but now I am dealing with a ...
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Multivariate Regression: Both Continuous and Categorical Predictor Variables

I am involved in a meta-analysis assessing the role of multiple baseline characteristics (e.g. age, BMI, symptoms and signs) in a given disease. One element of our analysis includes a multivariate ...
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What's the good way to find outliers in the continuous physical process measurements time-series? (picture attached) [duplicate]

What's the best way to find outliers in the time-series like the one attached? Just using the knowledge that it is a measurement of a continuous physical process. The data is quite short (200-500 ...
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Can we normalize both continuous and discrete numerical values

I have a sensor dataset with 16 features as numerical values (12 are continuous and 4 are discrete). I am using LSTM model to fit the data and do some classification. As both continuous and discrete ...
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How to estimate the optimal cutpoint for a binary outcome in python?

I have a dataset of diabetic patients which has been used to train an xgboost model in several outcomes such as stroke, amputation, and more. Originally we used the continuous numeric variables as-is, ...
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What's the best way to find outliers in the time-series, encountering that it is a real-world mechanical process (process continuity)?

What's the best way to find outliers in the time-series, encountering continuity? I attached two time-series that I'm interested to filter. One is less noisy, and one is a bit noisier. I'm mostly ...
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Interpreting logistic mixed model estimates of a model with continuous and categorical predictors

Newbie here. Sorry in advance if I express poorly as I don't completely master yet the vocabulary of statistics! I am performing a logisctic mixed model - with glmer - which presents as follows: CE ~ ...
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creating a continuous variable from ordinal variables

Could I simply sum up ordinal variables (some 4-,some 7-scale) to create a continuous dummy variable, and include it in a regression model? E.g. ...
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1answer
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Stratify Cox Proportional Hazard Model on continuous variable

I have a question regarding Cox proportional hazard models. I've been working with data with some time-varying variables and some that are fixed over time. In total 79 units are surveyed giving around ...
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Years as continuous variable [duplicate]

Can I use "years" as a continuous variable ("years" as calendar years from 1984 to 2014) to see if NDVI (normalized difference vegetation index), of the same area at the same time (...
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Positive or negatively bounded CDFs [closed]

If $X\in\mathbb{R}^n$ is a continuous random variable whose cumulative distribution function is ordinarily $$F_X(x) = \int_{-\infty}^{\infty} f_X(x) dx $$ what is the meaning of $$F_X(x) = \int_{0}^{\...
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How to conduct meta-regression with a continuous variable measured on different scales across studies?

I am conducting a meta-analysis on the efficacy of a specific type of psychotherapy for children and plan to use meta-regression to identify moderators. The predictor I am interested in is parent ...
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Sample size calculation for linear regression model with random intercept

I am trying to calculate the sample size for a mixed linear regression model. The dependent variable is continuous and the model includes 2 further continuous variables. The random intercept is based ...
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Deriving comparable probabilites from continuous and discrete data

I'm creating an elections index that's adjusted by how close the results are expected to be for a number of upcoming races in the US. My simulated results include discrete values like seat counts for ...
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Summarizing Likert-type Data

I used a questionnaire with several questions on a five point scale (never, rarely, sometimes, often, always) to determine how well a person liked their job. I then assessed the average scores for ...
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correlation between a continuous and a binary variable [duplicate]

I am interested between the correlation between a continuous variable and a binary variable (female=1/male=2). I think it doesn't really make sense to calculate it like this: ...
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137 views

How to check the correlation between categorical and numeric independent variable in R? [duplicate]

Just wondering if i need to check correlation between categorical and numeric independent variable in R, is there any specific package available in R. Or should i just find the correlation between the ...
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Why is measure theory needed to understand continuous random variables and probability density functions in particular?

Prefacing the question with the fact that I have no knowledge of measure theory. I would prefer a conceptual answer, as there already many mathematical ones. Also, why don't we need measure theory to ...
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Use different Naive Bayes classifiers to target different data

I am practicing using the Naive Bayes classifier to predict whether people get a stroke or not, but, I am confused with two classifiers. One is categorical Naive Bayes, another is Gaussian Naive Bayes....
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Does a random variable's distribution also carry over to its histogram-estimated probabilities?

If I have a finite sample of a continuous random variable $x$ as a vector containing $N$ observations, then I bucket those observations based on their frequency of appearance into equally-sized bins ...
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Mixed design with continuous between participants measure

Context: I commonly used mixed factorial designs that consist of two of more repeated-measures factors, that participants experience within the same experimental session, and a between-participants ...
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144 views

Do financial return series have a probability mass function (pmf)?

Stock returns, computed from stock prices as $r_t = \ln (p_{t}) - \ln (p_{t-1})$, are real-valued and unbounded giving the impression that they are continuous random variables. But aren't they ...
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Combine interconnected catgeorical and continous variable as predictor

I have two independent variables in my model, where variable 1 indicates if a product was listed on the homepage (0-1 coding, where 1 = "yes") of an online shop and variable 2 indicates the ...
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multiple regression with continuous and binary regressors

How can I do a multiple regression if I have continuous and ordinal (binary) (eg. male and female) regressors. Can I just add them like this lm(y~x1+x2+x3+x4, data=data)?
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Gaussian Mixture Model $p(x_i | z_i = k)$ a likelihood or probability?

In Gaussian Mixture models, the probability of observing the data $x$ given that it was generated from $M$ gaussian models is given by the following equation $$p(x) = \sum_{k=1}^m p(x|z=k)p(z = k)$$ ...
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Why do continuous data distributions have entropy of negative infinity?

Entropy is intended for discrete random variables, while differential entropy is used on continuous r.v.'s. This question is the opposite of another similarly titled question about discrete data and ...
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134 views

GLMM hurdle model for continuous data -Truncated negative binomial family in glmmTMB?

I am running a hurdle model using the glmmTMB function. My dependent variable is continuous and >= 0. I was looking for a function that would allow me to model the binary response in a logistic ...
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Is a bounded real-number random variable discrete or continuous?

A discrete random variable is countable (such as integers and natural numbers), whereas a continuous r.v. is not countable (like the real numbers $\mathbb{R}$). If I have a dataset whose observations ...
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Combining categorical and continuous features for neural networks

Is it OK to combine categorical and continuous features into the same vector for training deep neural networks? Say there is a categorical feature and continuous feature that I want to feed into a ...
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66 views

Two dependent uniformly distributed continuous variables and Bayes' theorem: a billiard table exercise

I am trying to solve the following exercise from Judea Pearl's Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. 2.2. A billiard table has unit length, measured from ...
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1answer
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Is it possible to take the Root Mean Square Error of a continuous function?

I am familiar with the Root Mean Square Error (RMSE) of discrete data: $$\text{RMSE} = \sqrt{\frac{1}{N} \sum_{i = i}^N |{\hat{y_i} - y_i}|^2}$$ where $\hat{y_i}$ are "predicted" or measured ...
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What happens if validation/real data has values outside training set limits for continuous data?

Describing Example: If feature X1 in training data has values inside [0,1] However, X1 in real/validation data has values [-1, 2[ What happens then? Previously discussed On previous discussions with ...
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Categorising a continuous variable for Cox proportional hazards analysis using “quartiles by event”

A colleague just told me that he categorises continuous data in survival analysis using "quartiles by event". He essentially uses cut-off points that equally distribute events into four ...
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1answer
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Can a Gaussian Mixture model be fit with a continuous response variable?

Does the Gaussian Mixture model require binary and multiclass response/target variable (classification), or can the target vector consist of all real numbers (continuous variable, regression)? Why is ...
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generate rules/features to identify which columns of an unknown dataset are categorical columns

I am working on the binary classification problem, in which I have to classify whether a column from a dataset is categorical or not. I am forming features for each column using rules like, 1.ratio of ...
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1answer
71 views

How to fit distributions to data in R?

I have 6 sets of Volume(v) & Duration(d) data. I have fitted a quite few distributions to the data such as Weibull, Gamma, Log-Normal, Exponential, GEV, Pareto, Log Logistic, Poisson, and GP. This ...
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What statistical analysis should we use for this aviation study?

I am helping a friend with an aviation research study. We have two categorical variables for our IV (Group 1 consists of low-cost airlines, Group 2 consist of legacy carriers), our dependent variable ...
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Relationship between ordinal and continous variables

How can I find out if there is a relationship between these two variables: x1 (ordinal) and x2 (continuous), this is a portion of my data: x1 x2 severo 0,688 severo 0,879 leve 0,75 leve 0,775 ...
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Power calculation for a one-stage, single arm trial with continuous primary outcome

An early-stage single-arm clinical trial is being planned to evaluate the efficacy and safety of treatment for a bacterial infection. The primary outcome is binary - proportion with >0.5 log10 ...
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How to deal with ties to fit data into continuous distributions in R?

I have rainfall duration and volume data. the duration is ...
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Distribution of X+U when X is a discrete and U is a continous random variable

Suppose $X$ and $U$ are independent random variables. $X$ is a discrete uniform variable and $U$ is a continuous uniform $[0,1]$ variable. What is the value of $\mathbb P(X+U\leq y)$, where $y$ is a ...
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What is the difference between discrete and continuous data?

I have two datasets: one consists of expected values and the second includes observed values. I want to test the difference between these two datasets. This is dataset A ...
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Consistent estimator of E(Var(Y|X)) for continuous random variables

Consider a set of $n$ i.i.d. observations $\{(x_i,y_i)\}_{i=1}^n$ of a pair of random variables $(X,Y)$ with finite mean and variance. I am interested in estimating the unexplained variance $\mathbb{E}...

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