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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3 views
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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0answers
9 views
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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1answer
11 views
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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21 views
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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2answers
45 views
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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1answer
24 views
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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14 views
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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0answers
32 views
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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23 views
Strategies for predicting values of a time-dependent CDF, given covariates
I've got data that looks like this:
...
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18 views
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
20 views
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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1answer
14 views
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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0answers
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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0answers
13 views
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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0answers
16 views
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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0answers
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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0answers
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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0answers
16 views
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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0answers
7 views
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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25 views
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
14 views
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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0answers
31 views
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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0answers
10 views
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 ...
3
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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
19 views
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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20 views
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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0answers
14 views
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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2answers
71 views
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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0answers
16 views
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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0answers
11 views
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
19 views
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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0answers
36 views
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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0answers
27 views
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
17 views
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
23 views
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-...
1
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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
97 views
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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0answers
13 views
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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0answers
22 views
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 ...
