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 ...

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19 views

Implication of peculiar data set

I've got a dataset which has exactly the same values for the regressors for two of the eight geographical regions but different values for the response variable. What implication does it have on a ...
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1answer
32 views

mixed models: wrong random intercepts and interpretation issues

I have a dataset of individues that participated in several races, but not all individuals did every race. Of every indivual I have their average speed. My goal is to have a measure of how difficult ...
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0answers
16 views

How to model the following dependent variable? [on hold]

If I got a dataset which the (count data) dependent variable has the following distribution, how should I model it? I am aware of the zero inflated model and the negative binomial model, but are ...
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0answers
9 views

Principled way of collapsing categorical variables with many categories

What techniques could I use to optimize the collapsing of many categories to a few, for the purpose of using them as an input to a statistical model? Consider a variable like college student major. ...
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25 views

Mathematical modeling basics

I have devised an equation for depicting the online activity of users. I shall not be able to disclose the equation here, but it basically is the sum of the weighted means of each activity (activity ...
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0answers
21 views

Prediction modeling for unbalanced and repeated data?

The following data is about virtual driving tests (t1, t2, t3) either theory (T) or Practically (P). This data is stored from online system. I am trying to develop a real-time system that will predict ...
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59 views

What methods can I use to aid in modeling a smaller data set when I have a significantly larger data set with fewer variables?

I currently have a data set with about 4,000 rows. The current model I have established for it is not very good, and I am going to receive more data for about 150 of these points, and I'm hoping that ...
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17 views

R model formulae

In case of R model building, one should almost always use formulae, but these are not wholly clear for me. Could anyone recommend me a good summary or tutorial? Besides, I have a concrete question: ...
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12 views

Setting Rolling Performance Window

I am in the process of developing a predictive model. I need your help understanding rolling performance window. The objective of the model is to identify customer attrition in retail segment. ...
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8 views

How can one incorporate prior knowledge about the distribution to which a feature conforms into a machine learning model to improve its performance?

For example, if I were building an SVM to predict whether or not a person is a professional basketball player, and I knew that height (one of the features available) were normally distributed, how ...
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19 views

Bayesian process with noise?

Does anyone know of any research considering Dirichlet processes (or other Bayesian nonparametric models), where sample points have a known gaussian noise attached to their input? I.e. I have a set ...
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0answers
72 views

Are all models useless? Is any exact model possible — or useful?

This question has been festering in my mind for over a month. The February 2015 issue of Amstat News contains an article by Berkeley Professor Mark van der Laan that scolds people for using inexact ...
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12 views

how to interprete the ACF/PACF plots? [duplicate]

what the result suggests of the order of the ARMA model?
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9 views

Need some help on discrete valued time series forecasting?

I have data on reservation requests for hotels (your booking information:searching date, check-in, check-out, # of rooms and etc. on hotel booking websites) and am trying to do some analysis on one ...
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1answer
132 views

Different shapes of an ROC curve

What are the possible shapes of an ROC curve? Is it necessary for an ROC curve to be shaped like a normal distribution curve? Can we regard the following two curves as ROC with the area under the ...
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0answers
13 views

Generating markovian paths

given a 4 by 4 transition matrix P, I want to simulate m Markovian paths of length n I created this function can anyone tell me if this is is correct ? ...
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1answer
50 views

Statistical models for Obesity data

I have a data on obesity status of women in a country. This data is based on across sectional study. Now I want to find the determinants of obesity among the women. Here dependent variable is binary ...
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1answer
39 views

Studying complex systems (complexity)

Complex socio-technical systems is one my research interests. Since I plan to further study such systems and related phenomena, I've done a bit of reading and ran across various books, such as Bar-Yam ...
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12 views

Cox MSM or Recurring Event?

I have dataset containing clients' history of active and inactive periods (if there is any) up to present day. Also lots of info as time dependent covariates. I want to model this as MSM, where both ...
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1answer
39 views

Help constructing a simple regression model with a breakpoint

This is related to my questions here and here. I am still struggling with my model, so I am taking it back to basics. My assertion is simple, I believe that watershed runoff will have a different ...
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26 views

What do you do with outliers when developing statistical models?

I am a beginner so I have an extremely tough time dealing with outliers. I wanted to ask the community to help me understand rule of thumbs or anythng that would help me deal with these questions ...
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0answers
12 views

How to label observations based on latent class analysis

I perform a latent class analysis to a dataset of binary variables with ...
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1answer
25 views

Designing an experiment for a marketing campaign using Incremental Response Modelling

I have the following hypothetical question, can anyone provide some clarification? I'm looking at designing an experiment or modelling what steps can be taken to maximise the Net Incremental Revenue ...
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1answer
46 views

How to decide whether a variable belongs to a linear model?

I have a set of inputs $x$ and noisy outputs $y$. I think that either $$y = a_0 + a_1 x$$ or $$y = a_0 + a_1 x + a_2 x^2.$$ How can I determine which model was more likely to have generated the data? ...
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1answer
37 views

Methods for determining cause and effect relationships between time lagged variables?

As you know, one can use regression for inference to learn which variables correlate with a response variable if the input predictors and the response share the same time frame. Let's say a predictor ...
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6answers
120 views

How to prevent collinearity?

Ieno & Zuur 2015 describe a number of causes of collinearity among explanatory variables entered into a linear regression. One of these causes is what they call a 'data collection' cause. They ...
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2answers
62 views

Are (some) time dummies redundant if another variable controls for a part of the sample period?

For an OLS regression, on the one hand, I have a dummy variable for each sample year (from 2000 to 2012). On the other hand, I have a binary variable that is 1 if observations refer to a concrete part ...
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7 views

contrast coding of nominal predictor variables by mean of the response

What is your opinion of contrast coding of nominal predictor variables by mean of the response variable? Let's say one has a data set with nominal values of sunshine (cloudy, mostly cloudy, mostly ...
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1answer
54 views

Multilevel Modeling in stata

I would like to make a model that calculates the probability of disease. Range of variables are following: disease ~ (0, 1); score ~ (1-10); test ~ (0-30) Large values of test and score indicates that ...
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45 views

How to statistically validate a Framework?

I am creating a Framework, that has independent variables A and B. It has dependent variables C, D, E. F, G, as shown in the diagram. Framework I understand that only after validating a Framework we ...
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1answer
38 views

Pitfalls in Fitting Nonlinear Models by Transforming to Linearity

Some nonlinear models can be transform to linear models. My understanding is that there might be one-to-one relationship between the estimates of nonlinear model and its linear model form but their ...
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18 views

Qualitative and quantitative effects

I am studying two different types of fees in contracts (both types are usually present in any contract). Each type can be x (fixed) or v (variable). Since no contract is mv (the first (second) letter ...
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1answer
42 views

Model comparison between glm (with Firth correction), random Forest, penalised SVM

I am currently developing three models to classify features of gene sites. I was using glm (with Firth correction), random Forest and SVM to build the models and I used forward and backward ...
2
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1answer
36 views

Comparing linear and nonlinear models

Is it possible to compare between these two types of model? I have a set of data that involves 6 independent variables and 1 dependent variable. It is based of a questionnaire for social science ...
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0answers
7 views

Approach to plotting a shock model with a Poisson parameter?

I know the shock model is defined as: $$ A(t) = \sum_{i=1}^{N(t)} A0\exp[-a(t-sn)] $$ where: $a = 0.5$ N(t) is Poisson ~ lambda, and lambda = 4 $t = 5$ $A0$ is given its own uniform ...
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61 views

Modelling flight delays with negative values

Modelling flight delays with negative values I am working on a model to predict whether a flight will be delayed. The data consists of some explanatory variables for flights from a specific airport. ...
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0answers
22 views

Prior for a linear transformation matrix: Matrix Normal Distribution

I have been trying to derive some conditional distribution for parameters of a linear transformation (represented as a matrix) and I had a lot of help on this thread yesterday. However, I realised I ...
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0answers
24 views

Device Comparision: Correlated or uncorrelated measurements

Background: I want to compare two devices measuring a certain characteristic on a subject. Thereto, each subject is measured once with device A and once with device B. It needs to be assumed that ...
0
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1answer
22 views

Costs in a game [closed]

I am trying to find the best model to solve the following problem: I have various players in a network. I have to visit all these players in the network. The players are visited in an optimal route, ...
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0answers
11 views

Comparing the impact of 2 independent variables on the dependent

I'm using a predictive modelling technique which has 2 parameters. I've performed a sweep of values for each of these 2 parameters, running each permutation of parameters 30 times as the technique is ...
2
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1answer
31 views

Choosing among PDFs

This is a pretty broad question. I just learned that two random variables can have the same moments but different PDFs. Take $\mathbb{E}[X_i] = \mu$ and $\mathbb{Var}[X_i] = \sigma^2$. Since there are ...
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1answer
97 views

Parameters vs latent variables

I have asked about this before and have really been struggling with identifying what makes a model parameter and what makes it a latent variable. So looking at various threads on this topic on this ...
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0answers
17 views

Zero-inflated negative binomial regression: 0 probability of a count greater than 0

Zero-inflated negative binomial regression assumes 0s are generated by two processes: a group whose counts are generated by a negative binomial regression and a group who have a "0 probability of a ...
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0answers
15 views

Help forming a VAR model

Can anyone help me for a very basic VAR model for regressing Inflation (CPI first difference) on energy prices and money supply. any suggestions be appreciated.
3
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2answers
109 views

Justification for using a zero-inflated negative binomial regression

I'm trying to describe in words why I used a zero-inflated negative binomial regression instead of an negative binomial regression: To model my data I used a negative binomial regression. However, as ...
2
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1answer
56 views

How is ABC more computationally efficient than exact Bayesian Computation for parameter estimation in dynamical systems (ODE) models?

Approximate Bayesian Computation has been suggested as an approach to parameter estimation for computationally intensive simulations, most commonly in population genetics, but also in dynamical ...
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1answer
63 views

Larger p-values but less misclassification error in Logistic Regression

I was doing logistic regression in R on 'Smarket' data set available in the ISLR library. Since correlation between variables were less, I used all variables in my model and I was getting the ...
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0answers
13 views

Binary outcome and correlated predictors

I have binary outcome variable (infection yes/no), two types of predictors, correlated (CRP 1, CRP 2 and CRP 3) which can be numeric or binary (it's pretty same to me) and uncorrelated predictors ...
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3answers
39 views

How to predict categorical reponse?

I am trying to predict categorical response by using several categorical variables and quantitative variables? I tried linear regression model in R, but I don't think it works well as the response is ...
9
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1answer
156 views

Additive Error or Multiplicative Error?

I'm relatively new to statistics and would appreciate help understanding this better. In my field there is a commonly used model of the form: $$P_t = P_o(V_t)^\alpha$$ When people fit the model to ...