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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country-time dummies and specification error

Currently, I am doing research about the impact of free trade agreements to trade flow. I have panel data that consist of 86 countries from 1980-2012. I use panel data estimation : Pooled Least ...
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1answer
39 views

Decision trees for advertising data

Assuming a dataset with the following attributes: Date (truncated), f1 ... fn, ...
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2answers
46 views

Best practices for extrapolating data

I have a set of variables that parameterize a logistic equation bacterial growth model. The parameters change based on temperature (e.g., growth speeds up at higher temperatures) and so it is ...
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17 views

How to maximize (optimize) a response, given only a dataset of responses and features?

Let's say I have an n x p dataset. For each n, I have the response, 'y', and p - 1 features associated with it. What is the best way to determine the values of the features that will maximize 'y'? The ...
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16 views

Cormack Jolly Seber - remove capture histories of individuals only encounter at initial capture?

Considering that parameter estimations in a CJS model (detection probability and survival) are developed using a capture history observed after the first release, is it not appropriate to remove ...
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17 views

Hierarchical choice modelling

I am trying to model students choices on studying from year to year and was thinking that a HLM would be the way to go, however I have become stumped in how to progress. The variable I am trying to ...
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1answer
29 views

Addressing Non-response in a Convenience Sample

I am studying customer satisfaction in a large hierarchical organization. I plan to administer a voluntary survey to customers across the organization, and need to address non-response in my analysis. ...
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27 views

how to compute odds ratio

Given a generic classification model $y=f(x_1,x_2,..,x_p)$ where $y\in \left\lbrace 0,1 \right\rbrace$ is it possible to compute the odds ratio for each variable? A theoretical explanation and ...
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8 views

BRT predictions on zero-inflated gaussian fish abundances include negative results

hopefully someone can point me in the right direction here. I'm using boosted regression trees (BRT) to assess the relative importance of a number of environmental factors (sea bottom temperature, ...
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2answers
53 views

Modeling user behavior in a system

Consider a system, where each user enters the system, performs a series of predefined actions, and then exits. For instance, consider a system with 5 predefined action. The action log of some user is ...
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10 views

Using AIC to select an upper bin for a counting variable

I have some patient data and I'm using a logistic model to explore factors that might affect a patient considered severe/not severe for a disease (the DV). Many of the variables are counts; counts ...
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77 views
+100

How to fit this neuron firing model with R?

I originally posted this as an answer elsewhere but in retrospect it seems more like a question: What is the sample-size range for which the median should be preferred to the mean as a measure of ...
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1answer
47 views

logistic regression for modelling

I have these data plotted above. The explanatory variable represents intensity levels of ground shaking at different locations in an earthquake, and the response variable represents amounts of ...
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4answers
356 views

Fitting probability distribution to data

I am trying to fit a model for the values plotted above. The explanatory variable represents amounts of compensation claim in an earthquake, and the response variable represents amounts of ...
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14 views

survey data feedback normalization

assume i have a survey which contains 10 questions, for each question one can answer helpful/not helpful/neutral. when i finish collecting the data, i discovered that some people tend to have a lot of ...
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1answer
37 views

Cost Benefit Analysis of Pre-screening Widgets for Faults before they Fail

I want to build a model that determines whether to pre-screen my widgets for defects. If I do pre-screen, it costs a fixed amount per check and I resolve the problem 100% of the time. If I don't ...
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0answers
17 views

Asymptotic Property of the Likelihood surface

I have a questions which I am not quite sure how to frame, so I apologies if it does not make sense, but I will try my best to make it interpretable. I have been running some network models in R, ...
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2answers
98 views

$p(D)$ in Bayesian Statistics

Say I have the following obvious Bayesian computation: where $\theta$ is a model parameter that we try to infer and $D$ is observed data. I have always understood $p(D)$ to relate to knowledge ...
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1answer
34 views

Forecast Daily Data with Multiple Seasonality [duplicate]

I am new to the field of time series forecast and trying to build a time series model on R for a daily data, which I think there are multiple seasonality, weekly and monthly. My data contain the ...
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1answer
17 views

normalizing dataset for extrapolation - sample or population mean and standard deviation?

I am currently fitting models that are intended to be used for extrapolating from a limited sample to a large population. For a specific example, one model is predicting water temperature in rivers ...
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80 views

How many people bought wine?

Rephrased a problem trying to solve for work in terms of people buying wine, also included progress made so far. Set-up: Customers enter a winery with the option of buying bottles of wine. Those who ...
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1answer
48 views

Estimating Negative Binomial Regression Model

It is easy to estimate a Poisson regression model using the Newton–Raphson Iterative Technique as it only involves one parameter (mu). However, I am unable to understand how a negative binomial ...
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3answers
132 views

Multiple Regression and number of parameters to include for a learning algorithm

I am quite new to Machine Learning and come from a computing background. I have a quite big set of features (~50) with about 4k observations. Is it correct thinking to include all of them in a ...
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0answers
57 views

how to code and interpret categorical time varying variable in Cox PH model

I'm working on a project looking at the relationship between exposure to several different drugs on the risk of preterm delivery in a cohort of pregnant women with a particular disease. I'm confident ...
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2answers
106 views

Are there any probabilistic models for graph-based recommender systems?

All I can find now is somehow based on random walks or graph kernels, which is nice, but I want to have a more or less solid probabilistic foundation for my recommender system for bounds and ...
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2answers
56 views

how to deal with nominal variable with too many levels

Hi currently Im trying to modeling a response variable y, and i have zip code as my independent variable, my model is logistic regression. when come to nominal variable, the text book method is to ...
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1answer
166 views

Categorize continuous data effectively (taking into account a response variable)

I wonder what are the better approaches to categorize continuous data (e.g. age) than dividing them with the use of quantiles and cut function (in ...
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23 views

Cross-estimating the independent variables to exclude outliers

Purpose: pragmatic data mining and prediction, NOT for publication or science Data: observations from nature, so a high degree of stability is expected in the relationships N: approx. 15 k I am ...
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71 views

Time series modeling with R on weekly data

I am trying to do time series modeling and forecasting using R based on weekly data like below - ...
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21 views

How to model two variables with a cumulative exponential relationship?

Suppose I have a response variable(y), which is normally distributed, and y is generally changed with ...
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0answers
46 views

Spatially explicit model to test effects of multiple variables

What is the appropriate model to test the effects of location, species, and size on tree growth? So I have both categorical and continuous variables I want in the model. The following graphic just ...
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1answer
43 views

Modeling techniques for dichotomous data

I have dichotomous data where some of my independent variables are categorical, some are continuous and some are binary (0/1). My dependent is a binary response (Fail/NoFail, 0/1). The data is some ...
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0answers
36 views

Does it make sense to impute missing covariate data when the imputed value is a function of other covariates in the regression model?

We are building a model that adjusts for standard covariates (e.g., age, gender) and for the outcome at baseline. It would be ideal to adjust for each subject's baseline value like so: $$ Y = ...
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34 views

R code for predicting part fitments from the following dataset

I'm a manufacturing engineer trying to resolve an issue regarding non fitment of parts. There are a couple of components which have dimensions x1 to x6 (data below). Upon assembly, they form ...
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19 views

What is a forward/inverse model?

The term forward model comes up a lot when reading about Bayesian modelling. I am yet to understand what exactly is the forward model? Is it the model that describes the output/observed variable and ...
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1answer
29 views

Identifying subset of variables with most predictive power of the other variables

I have 31 numeric variables (e.g., A-AF) for which I am attempting to identify the smallest subset of those variables that will predict the values of the remainder of the variables with a CI of 90% or ...
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1answer
52 views

Ratio estimation model in 2-stage cluster sampling

I've been reading about stratified sampling, 2-stage SRS sampling, and ratio estimation in finite populations and I have a question. When the ratio estimator is introduced, it seems that in order for ...
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1answer
68 views

Regression model for prediction using intermediate outcomes

Is it appropriate to include intermediate outcomes in a predictive model? It is quite clear that one should not control for post-treatment variables / intermediate outcomes when the goal is causal ...
2
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1answer
38 views

What test to use here?

I have a model created from a prior dataset and I want to know if it can be used on my current dataset. The original model gives the expected percentage of times an email is opened x hours after it ...
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1answer
41 views

Frequency weighted least square estimation

I recently realised an RLS Algorithm which fit a stepresponse of a system with an underdamped complex pole pair. Now i realised that there is a bias for some kind of responses i get. I found out that ...
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1answer
47 views

Detecting 'causality' in Likert-time series data

[Note] I've decided to re-write my question for the sake of brevity. The original question can be found below. Suppose a number of individuals fill in a questionnaire at a multiple number of time ...
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1answer
63 views

Fitting distribution to spatial data

Cross posting my question from mathoverflow to find some stats specific help. I am studying a physical process generating data which projects nicely into two dimensions with non-negative values. ...
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1answer
31 views

Help in viewing the output structure of a neural network

0 down vote favorite 1 I used nftool in Matlab 2012 and trained a network. I gave the training inputs as x=[250:1] and targets as t=[250:1]. I used 10 hidden layers. I trained the network and got the ...
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0answers
19 views

Expectation-Maximization (EM) method for parameter estimation using fuzzy logic

I am sorry if my question is not fit here. If so, please recommend me the correct forum. I am thinking of estimating a fuzzy model using the EM method. I have a set of observations from a nonlinear ...
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0answers
71 views

Fit tide data to a sinusoid function

I am trying to fit to a long series of data about tide to a sinusoid function. I would like to have on the y axis the height of the tide (from $-$2 m to 5 m) and on the x axis the time in hours 24h.I ...
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0answers
18 views

Need to build a model to see the submersion time

I need some help since it is not long time I am using R. I have one year, every day, twice a day (every 6 hours) on tides. I would like to model this in order to check the submersion time of some ...
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96 views

Radial profile and 2d log-normal distribution?

I have a case study where a person should be located. We do not know where this person is, but we have some information. The total story is basically about the person which is to be searched. The ...
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2answers
430 views

Why would a statistical model overfit if given a huge data set?

My current project may require me to build a model to predict the behavior of a certain group of people. the training data set contains only 6 variables (id is only for identification purposes): ...
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0answers
29 views

Simulate microarray technical error

I need to simulate some microarray experiment datasets. I have the levels of expression of a set of synthetic genes in different experimental conditions. For simplicity of the method this levels are ...
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1answer
71 views

Statistical modeling terminology

Based on Wikipedia's definition, I believe that statistical model refers to a certain sort of family of distributions, such as univariate Gaussian distributions in general. Is there special ...