Predictive models are statistical models whose primary purpose is to predict other observations of a system optimally, as opposed to models whose purpose is to test a particular hypothesis or explain a phenomenon mechanistically. As such, predictive models place less emphasis on interpretability and ...

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Classification tips for a begginer

I'm doing a graduation work that involves applying Classification algorithms in a dataset of matches from Dota 2 (a popular MOBA game). Here's an explanation of the problem: Dota 2 matches are played ...
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How to compare fit of discrete process with discrete underlying process?

I am basically looking for an equivalent to something like an $\mathbb{R}^2$ for a model on a dataset that is itself simply a collection of points. That is, if my data set is (trivial example): ...
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How to evaluate a trained model using parameters other than AUC in RapidMiner?

I am using RapidMiner to build predictive models trained and cross-validated by a set of medical data(65 cases. 18 attributes), I am now running trials by trying different combinations of learners and ...
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Prediction vs. Explanation and its Effect on Statistical Methods [duplicate]

In layman's terms, what is the difference between predicting and explaining in statistics? I was looking for the differences between AIC and BIC and found this post with an answer stating: My ...
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Call Centre Models

Can anyone suggest me, which Mathematical(Statistical) methods can be used to predict incomingcalls by a given time interval at a call centre? Please cite any ...
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30 views

Understanding the Rank Probability Score

The ranked probability score (RPS) is a measure of how good forecasts that are expressed as probability distributions are in matching observed outcomes. Both the location and spread of the forecast ...
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43 views

Removing the intercept term in a dynamic regression justified?

I'm trying to build a cross-sectional prediction model (dynamic panel) with the following form: (including a LDV) $Y_{i,t+1}=a+bY_{i,t}+cX_{i,t}+e_{i,t+1}$ As the sample contains for example ...
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100 views

How to form a predictive model in R?

I have two data sets whose structure is like this: DATA SET 1: ...
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55 views

How to develop a prediction model based on correlation in R?

I have two sets of data, say sales and profit, and I have calculated the correlation between these two data over different months using R. So currently I have ...
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37 views

Evaluating predictive models

I am looking for ways of evaluating the performance/success of predictive (classification) models for economic purposes. I know of: Direct accuracy percentage AUC score Net profit Rate of return ...
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Different sufficiency condition for Goods and bads

I am building an underwriting model for a bank with the following construct Development Sample Window - Accounts opened before Jun'13 (i.e. have completed atleast 12 months as of Jun'14) Bad ...
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27 views

Predictive Model from Counts Data

I have some data that is the number of times a person visited a doctors office over a course of $5$ years. I want to create a model that would be able to predict the most likely number of counts that ...
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48 views

Cross-validation with dummy variables?

Does it make sense to use cross-validation with factor variables that have 3+ levels? When using bestglm, I get an error saying that it doesn't work with categorical variables. In the documentation ...
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289 views

Predicting the Weather

Given a tree trunk with concentric circles, can we predict the weather for each year? Each concentric circle accounts for a year that the tree has been on the Earth. The innermost circle is the oldest ...
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GBM, it's overfitting/multicollinearity problem and parameter setting up

I recently came across a predicting problem (0-1 outcome, with more than 80 variables), I decided to use GBM (Gradient Boosting Machine by Friedman)to handle this job. I let the GBM use only 70% of ...
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28 views

Is this poor transformation advice for predictive modeling?

I have gotten some advice from a PhD statistician on doing predictive modeling on large datasets (lots of variables AND lots of observations) that I should perform transformations to eliminate ...
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60 views

Forecast with predictable market events

I'm trying to build a predictive model to forecast the residual value of used electronic equipment. As a first step, I created a few quick plots in order to visually identify any interesting features. ...
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38 views

How to preform non-parametric bayesian based regression (predictions) in R?

I am working on some non-parametric bayesian based predictive analysis using R. I have a set of data which denotes various parameters of an online transaction. Based on these parameters I want to ...
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9 views

Values in predictors have same pattern for two possible value in dependent variable?

I am trying to build a model for auto rejection of crowd-sourced task (eg: human name transcription of census data). My data set has 5 predictors, and dependent variable is either correct or ...
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44 views

How to avoid random forest overfitting and improve prediction?

I have an input dataset x_train and an output dataset y_train ...
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30 views

How does Vowpal Wabbit handle NA's or missing values?

I'm working on a problem that involves a large amount of NA's. How does VW work around this? Should I try to impute the NAs with colmeans or something similar before piping into VW format?
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31 views

Concordance vs. Sensitivity

I am confused between these two terms: sensitivity and concordance. What I understand about these two terms: Concordance: the number of pairs where actual 1s have higher predicted probability of ...
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75 views

Difference between prediction in R and SQL

I'm working on a prediction model for a continuous variable (amount of medicine injected) .I use R for modeling.My project flow is to multiply the prediction of a glm (logistic regression) model that ...
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24 views

Modeling Counts With Small Observations

I am new to Cross Validated SE so I am going to try and formulate my question to the best of my ability. I have a large data set that contains $5$ different fields. The fields are ...
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1answer
25 views

Model specification with Deflators: methodological question on forecast model

I am trying to build a model to predict one year ahead Earnings per share $(t+1)$ based on variables in year $t$. I’ve seen a lot of models in practice that use the following methodology: ...
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27 views

Out-of-time testing (basic question)

I understand the importance of out-of-sample testing, but could you tell me why I should (or shouldn't) do out-of-time testing ? The only use that comes to mind is if the predictive model applies to ...
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39 views

Using OLS for Model Selection and Prediction - Heteroscedasticity Issue

I am new to regression and having problem in solving Heteroscedasticity in OLS. Have done lots of homework and test before seeking your advice. Sharing the background and what I have done to solve the ...
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Predictive modeling techniques for in-sample rather than out-of-sample prediction?

Is it appropriate to apply predictive modeling variable selection and shrinkage techniques (for example, ridge regression or lasso) for in-sample prediction rather than out-of-sample prediction? ...
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Calculating upper and lower confidence limits on a population estimate derived from multiple point estimates

I am generating a river reach population estimate for a freshwater mussel by summing point estimates made across a gridded point network (within the reach) using a generalized linear mixed model ...
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178 views

How to evaluate fit of a logistic regression

I have a set of data points, which exhibit a solid linear correlation $r\approx 0.9$. I am basically plotting population in certain areas against the number of occurrences of a certain phenomenon (so ...
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88 views

Confusion between caret randomForest predict() results and reported model performance

This question seems related, but the consensus was that the issue had to do scaling the data, which I do prior to training, so I don't think that's the issue: Issue on prediction with FinalModel of ...
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21 views

Predict/impute one cell of matrix using all other cells

The question: I want to predict/impute one missing cell of a matrix using the contents of all other cells. Anyone have ideas on how to do this? The context: The matrix is n people's responses to m ...
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29 views

Estimating a distribution from a dataset with multiple parameters

How would you go about solving the following problem? You're an insurance company who writes workers compensation policies. You want to build a probability distribution for the number of annual ...
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40 views

Forecasting agricultural commodity prices with R

I would like to create a predictive model in order to forecast the price of an agricultural raw material. I got time series for the prices and the production of this raw material, and also for the ...
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2answers
36 views

What model would be appropriate for predicting electrical consumption given multiple (mostly) independent variables?

I have about 1000 samples worth of daily electrical consumption for a building. I'd like to build a predictor based on a number of observable inputs, including: daily temperature (continuous) hours ...
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135 views

Best method to predict binary outcome with multiple records per subject

I am interested in building a model to predict the binary outcome, retention (1 - retained; 0 - not retained) with various potential predictor variables (either continuous or categorical). With that ...
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32 views

Applying the Akaike Information Criterion to Data

I have some variables that I would like to run regressions on, to create a model, but I am unsure about how to actually AIC (or the BIC). Unfortunately I have not yet taken a mathematical statistics ...
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59 views

Anomaly detection using exponential weighted moving average

I would like to detect anomaly using exponential weighted moving average. I don't have series of data points. All I have is EMA(t-1) and the data point of the current time(t) DP(t). From these data, ...
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35 views

Definitions of Prediction vs. Predictor

I am writing an article which includes discussion of the MMSE estimator of the posterior predictive distribution. Since I use this term quite frequently, I was considering referring to this estimator ...
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21 views

What are some multivariate models with feature interactions

I have dependent variable matrix $Y_{i,j}$ and feature matrix $X_{i,k}$. My objective is to predict each element of the vector $[y_{i,0},...,y_{i,J}]$ by using new observations of the features, ...
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31 views

random forest and prediction

I am building a random forest model to make predictions. Response variable is treated as continuous but not really continuous, e.g., integers from 0 to 10. I have problems in constructing ...
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31 views

Possible inferences from a graph pattern

So, I had a weighted dynamic graph having info about 10 consecutive timesteps ( basically 10 files ). Now, I had to mine out patterns in the weight and structure of the complete graph. I did that. The ...
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39 views

Acronyms to use for Bayesian posterior predictive distribution estimators

I am considering writing an article that discusses the Bayesian MMSE and MAP of the posterior predictive distribution. I was wondering if there are acronyms that have been used so that instead of ...
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temperature prediction algorithm

I found an interesting problem in a contest on temperature prediction: https://www.hackerrank.com/contests/expansion-challenge/challenges/temperature-predictions It is not about forecasting the ...
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Taking into account Bayesian model uncertainty

I recently received a review of a paper from a Bayesian Statistics Journal. The Associate Editor wrote this mini-review (quoted below in full). The paper is talking about Bayesian modeling of DNA ...
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Recognize spatio-temporal patterns correlating with events

I am trying to recognize a spatio-temporal pattern in my spatio-temporal input sequence X. The occurrence of the pattern is roughly temporally correlated with another event E1. For example I have ...
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58 views

Creating a model for prices including supply

I'm working on modeling secondary market ticket prices for sporting events, but the issue I'm running into is that the model (a linear regression) assumes that more season ticket holders and more ...
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Forecasting: Different Model for 1 month, 2 month, 6 month forecasts?

I'm still trying to expand my statistics and forecasting technique knowledge. Right now I'm forecasting seasonal contact patterns, so the simplest model I can understand with seasonality is a ...
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Are world cup predictions testable?

As of today, dozens of soccer world cup predictions exist, some more complex, some more elegant, and most of them predict every nation's "chance" of winning a particular match/ the cup. As I am ...