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Questions tagged [modeling]

A statistical model is a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or more random variables. The model is statistical as the variables are not deterministically but stochastically related.

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Modelling probability distribution of a set of sequences (to calculate Entropy)

Let $T$ be a set of trajectories $\tau$, where $\tau=\{\mathbf{x}_1,\mathbf{x}_2,...\mathbf{x}_N\}$ with $\mathbf{x}_i\in\mathbb{R}^k$ being a vector of observations. I am looking for an efficient ...
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Building models from spatial data [on hold]

I would like to know which are the most accepted ways of introducing spatial data into a regression model. Let's say, for the sake of example, that we are getting an observation from each of the ...
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How to model a distribution from simple capital cost data?

I want to create scenarios for a simulation model I am working on. Someone recommended me a distribution and select instances to create different scenarios. But my data is limited. For example, my ...
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How to model a specific distribution using domain knowledge rules [on hold]

Suppose I have a variable Y that I want to predict with a model using predictor variables X1, X2 and X3. I have a large set of Y-data and from this I know with some certainty and accuracy the ...
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how to analyze time series data and mark if single data is seasonal or not seasonal

I have data set as shown. It is daily sales data for 4 different product for almost a year. I aggregated the sales of product for each day into . I plotted sales of 4 product as per date and got this ...
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How to use features in regression model with 2 of them in linear relation with the value to be predicted?

I am relative newbie to data science so please excuse me if its a trivial question. I have 6 features and want to predict the 'y'. These features are related to y in the training data-set as follows; (...
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Pricing transfer prices for oil hub? 390 Days of prices given

Need some input in how to attack this problem. Given are 8 timeseries: UK Oil price, Delivery Quarter 1 2020 UK Oil price, Delivery Quarter 2 2020 UK Oil price, Delivery Quarter 3 2020 UK Oil price, ...
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What is a good model for conditional data?

I am looking for statistical models of conditional data where some variables take certain values conditioned on values of other variables. For example, if $[x_1, x_2]$ are two variables defining a ...
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1answer
24 views

Comparing assault rates at one facility with two other facilities

Assaults on staff are fairly uncommon in our facilities with between 70-140 in a year at a given facility. Time, similar to 'person years' in epidemiology, is tracked as 'number of bed days' (i.e., ...
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36 views

Calibrating LASSO prior (how to select the scale hyperparameter)?

I want to use a LASSO prior (Laplace prior) for a location parameter $\mu$ $$\pi(\mu \mid s) = \dfrac{1}{2s}\exp\left(-\frac{\vert \mu \vert}{s}\right).$$ However, I do not know to calibrate this ...
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Nonlinear data to use in multiple linear regression?

I am supposed to be running a multiple linear regressions to test my hypotheses. However, when first testing the assumptions that should be met before performing a linear regression, it turns out my ...
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1answer
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Modeling a dataset with multiple predictor variable replicates for each response record

I have a dataset that I want to model with a single response variable (yield of a crop plant). However, I have multiple replicates of my proposed predictor variables, from multiple sampling surveys of ...
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Customer time series analysis

Statistically speaking, If I have 720 0000 unique customer information, how best can I sample from this population such that it is a representative of the whole data set? Also how large should my ...
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1answer
28 views

How powerful are second order interactions?

A lot of applications in statistics and machine learning model a phenomenon by second order interactions of variables and get good results. By second order interactions I mean, for a general variable $...
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26 views

Plotting Residuals vs Predicted Values

In textbooks, residual plots are described as have predicted (fitted) values on the x-axis, with the y-axis being the difference between the predicted and observed values. However, I'm having trouble ...
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Appropriate model for cross sectional study of firms [closed]

I am conducting a cross-sectional study of 99 UK firms in 2017. I aim to find a positive/negative effect between a board characteristic (diversity) and performance variables (i.e. ROA, ROA, EBITDA, ...
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1answer
32 views

How to generate mean curve of non-function?

I am currently working on curves generated in tensile tests of polymer specimens. Here, I try to generate a mean curve of five data sets generated at the same composition of the samples. Unfortunately,...
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1answer
13 views

Modelling rnbinom not returning pre-set parameters

I am working with the rnbinom function in R but I think I have misunderstood the meaning of the parameters that get stipulated in the arguments. For reference, I ...
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R : Can i use discriminant analysis with 2 groups in the context of predictig the success of bank telemarketing?

I have a school project having us working on the dataset 'data-driven approach to predict the success of bank telemarketing' provided by Sérgio Moro. A bit of background about the dataset: it's ...
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38 views

Understanding the DLM

The DLM model in my notes is described as: $f_k(\theta,u)=F_k\theta+u$ and $h_k(\theta,v)=H_k\theta+v$, where $F_k$ is a $d\times d$ matrix and $H_k$ is a $d'\times d$ matrix, respectively called ...
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1answer
22 views

Is this function monotone increasing?

I've made a simple model for temperature deviation in response to atmospheric CO2. The blue line shows historic temperature deviation data dotted line marks the point where I try to get the model(...
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23 views

Preparing a GLM logistic regression: choosing the factors

I am researching the incidence of pain after an operation, according to anaesthetic type. Univariate analysis is inconclusive, but I would like to proceed to multivariate analysis. I have done some ...
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One standard error rule multiple hyperparameters

The one standard error rule for selecting the hyperparameter value after a cross-validation search for the LASSO or ridge regression's $\lambda$ is widely known and used. Is there an analog for this ...
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How does one interpret r-sq (adj) versus deviance explained in GAMM creation?

I am running some models for my master's dissertation using backwards stepwise regression of GAMMs. I have six total models. I have a base model with several significant variables; the r-sq (adj) = -0....
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Survival analysis: Individuals with event time = 0, exclude or not?

Data set: 50000 participants Assessments of various risk factors at baseline Dates when participants were included in the study Dates when participants died or were censored (after 2 years) ...
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1answer
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On some confusion regarding the autoregressive model and the definition of a statistical model

Citing Wikipedia the stationary AR(1) model (without constant trend parameter) is defined as $$ \begin{aligned} y_{t} &= + \beta y_{t-1} + \epsilon_{t}, \\ \epsilon_{t} &\stackrel{iid}{\sim}...
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Nested or Crossed ANOVA?

I am uncertain of the model that needs to be used in this case (nested vs. crossed), so first I will present the problem and then I will ask my questions. I am interested in knowing if the total ...
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1answer
63 views

Are GLMs just glorified WLS regressions?

When performing weighted least squares $L = \frac{1}{2} \sum_i w_i r_i^2$, Aitken showed that one ought to weight each sample by the inverse of its variance $w_i=1/\sigma_i^2$. This leads to gradients ...
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How can I make a better formula to predict revenue? [duplicate]

I have data from an example e-commerce site and I'd like to predict the effect of a change in the average price per purchase and the change it will create for revenue. To start, I'd like to make an ...
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3answers
113 views

Interaction between dependent and independent variable

I am conducting a multiple linear regression on data from a cross-sectional study, and I suspect that there is an interaction between my dependent variable (a disease risk marker) and one independent ...
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1answer
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Difference between bivariate exponential family and bivariate elliptical family

I'm studying the elliptical family and I'd like to know the principal differences between the bivariate exponential and elliptical family.
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1answer
18 views

transformation of continuous variables in accelerated failure time model

Should I do some transformation of continuous variables in accelerated failure time model? In PH model it is needed and martingale residuals are helpful there. I know that PH and AFT models are equal ...
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Interpretation of a brier score

Suppose that multiple brier scores were computed for two models $A,B$ and the density of the scores plotted as Where the average of $A$ is less than $B$ What would the interpretation of this be? ...
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Randomized Block Design Models

I have been asked to fit the following models in R: The models are based on this data: I know the mediums are the blocks and the units of the active ingredient are the treatments. I understand how ...
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How is Logistic Regression related to Logistic Distribution?

We all know that logistic regression is used to calculate probabilities through the logistic function. For a dependent categorical random variable $y$ and a set of $n$ predictors $\textbf{X} = [X_1 \...
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How to align data series along x-Axis to achieve besst fit?

I have 4 datasets that I am trying to align to each other so I can so some further analysis. I asked a similar question earlier, that didn't get much attention, so I am trying again (this time with ...
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1answer
22 views

Forward Model Selection Using p-value

I know that it is not advised to use the p-value as the criterion in practice, but I am not asking about that. I am wondering how this p-value would actually be calculated. In other words: Forward ...
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how to handle non-independent experimental data

I have data to analyse that involves 12 treatments. Each treatment was "replicated" 3 times, for 36 observations. But the experiment involved applying the treatment to 1 side of an object -- and most ...
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1answer
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How do I estimate probability of success with no successes? [duplicate]

My $6$ friends and I tried buying tickets to a popular event. Everyone who wanted a ticket got a random number and if your number is less than or equal the number of tickets available, you can buy a ...
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Matching a quadratic model to a linear model to give constant false alarm rate

I have a linear model which estimates the false alarm rate on different regions of an image on thresholding. Meaning the rate of false alarms is constant for all regions when a single threshold is ...
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1answer
37 views

Can I have some help for Statistics/probability theory

Let $\Omega = \{0,1\}^{\mathbb{N}} = \{\alpha=(\alpha_1,\alpha_2,...):\alpha_i \in \{0,1\}\}$ Fact. There exists a $\sigma$-algebra $\mathcal{F}$ such that for every $\beta = (\beta_1,...,\beta_n)\in\...
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How do I formulate logistic quantile regression models?

Which of these models is most appropriate given the data (prediction is my goal), and why? I haven't had much experience with quantile regression, and I have so far assumed (probably niavely) that ...
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1answer
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Fitting a continuous normal distribution to an incomplete score distribution

Given a sample of data that contains only the score frequency distribution for scores below a certain threshold, is it possible to fit a complete normal distribution so to estimate what the will be ...
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1answer
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Model that can make a prediction (classification) based on a sub set of features

Model that can make a prediction (classification) based on a sub set of features What is the recommended approach, best model or algorithm that handles use-case where we want to predict based on sub-...
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1answer
36 views

Ordinal regression or multiple regression?

I'm using STATA and this page to find a proper test, but I'm not sure which is better fitting, an ordered logistic regression or multiple regression? My dependent variable is life quality (ordinal ...
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2answers
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Can I remove significant interaction variable in regression model?

I have a regression model, which consists of 4 predictors and 1 interaction - i dont know what are the correct symbols and terms, so I will drop my model here: ...
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Dynamic transformations on an inferred time-scale [duplicate]

Sorry if this is a duplicate, I have limited knowledge on data science, so I don't know the correct terms to look for and don't know if there's already an answer out there. I have two datasets which ...
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1answer
44 views

Estimation - Taylor's Stochastic Volatility Model

I want to estimate Taylor's stochastic volatility model (fit on stock data). Is there any package in R ? As far as I know, there is not a "standard" procedure in Eviews. Even a free-distributed ...
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How can MASE (Mean Absolute Scaled Error) score value be interpreted for non time series data?

If I have used MASE to calculate non time-series data error (as described by Dr. Rob Hyndman here), how can I know if the score received is good or not? Since it is not a time-series, a random walk ...