# Tagged Questions

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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### Unique (?) idea for forecasting sales

I'm working on developing a model to predict total sales of a product. I have about a year and a half of bookings data, so I could do a standard time series analysis. However, I also have a lot of ...
62 views

### Predicting for month in R

I'm trying to understand some concepts related to predictive modeling. So let's say that I have the following data sample and am trying to regress sales on ...
44 views

### Modeling pass rates for departments and courses within a school

Suppose I have a regression model, for example a logistic regression model, which provides a score between 0 and 1 reflecting whether or not that a student will pass a course given certain variables: ...
138 views

### Sensible to include ratio as a variable in logistic regression?

I'm creating a generalised linear regression using a binomial link function for two variables A and B. From looking at the data it appears that A/B may have discriminatory effect. Is it sensible to ...
122 views

### Shifted intercepts in logistic regression

I have a question about the effects of shifting the intercept in a logistic fit on the mean of a particular transformation of the scores. Here is the notation I will be using for the question. The ...
128 views

### Predicting a dichotomous variable

I have a series of descriptors, some continuous, some discrete and an output variable which is dichotomous. I have several parameters, but for the sake of simplicity let's say my data look like: ...
89 views

### Validating a logistic regression for a specific $x$

I have a logistic regression model for 0/1 binary response data that is built from samples $(x_1,Y_1),\ldots,(x_m,Y_m)$, where $x_1,\ldots,x_m$ are, fixed, nonrandom, real values and $Y_1,\ldots,Y_m$ ...
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### Choosing the best model to predict second hand widget prices

I am looking for some thoughts on how best to approach a dataset and pick the right model for predicting the second hand price of widgets. Some background on the properties of these widgets: The ...
140 views

### Autocorrelated predictors in linear models

I need to predict the outcomes of a time-series variable $Y$ based on two time-series predictors $X1$ and $X2$. For simplicity I will only illustrate $X1$ in the rest of this question. The ...
72 views

### Graphical nominal model

Suppose I have a set of $k$ matrices. $$\epsilon = A_1,A_2,...,A_k$$ Each column of $A$ is categorical vector. $$A = v_1,v_2,...,v_n$$ I want to find the mapping  f: A ...
80 views

### Confidence intervals for difference in time series

I have a stochastic model used to simulate time series of some process. I am interested in the effect of changing one parameter to a specific value and want to show the difference between the time ...
286 views

### Maximum of two (or more) gaussian distributions with known and possibly different means/variances

I am a software engineer by trade doing stats in my free time. I am playing around with an implementation of Microsoft's TrueSkill rating system for ranking players and openings in from a data set of ...
70 views

### Data Correlation for Predictive Basketball Model

Background Information: (scroll for question) Attempting to find correlation between the average number of fouls committed by each basketball team in a game and the referees calling the game. Such a ...
31 views

### Using sequential observations to perform online prediction

I'm trying to perform predictions from a sequence of events. My problem is this: Data collection: Suppose you can continuously observe a person sitting in a library. You take note of every time that ...
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### How to compare the accuracy of predictive algorithms when the predicted value contains measurement error

I am conducting (somewhat casual) research on the accuracy of several algorithms meant to compute a value when given a set of experimentally gathered variables, including time. The issue is, the true ...
76 views

### 95% CI or standard error of predicted risk in Cox regression using R

I am doing a multivariate Cox regression. I got the predicted risk for a new scenario based on the existing Cox model in R using function predictSurvProb in the ...
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I understand how the adaboost algorithm works to produce a prediction of a class, however one thing I haven't seen is how to get a measure of accuracy for that prediction. For example, if I fit a ...
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### Population genetics: analysis of allele frequency distribution along environmental gradients

Is there a software or a R package that does a simulation of spatial distribution of alleles? I'm interested in how a distribution of alleles of functional loci is shaped by a pattern of environmental ...
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### What is the difference between the values in the 'fit' attribute of a gbm object and values computed by gbm.predict?

My intuition is that the fitted values and predicted values of a gbm object should be identical. But in this example with just one tree, the values are different: ...
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### Measuring parameter sensitivity and variability (standard-error) in k-fold cross-validation

I mainly use k-fold cross-validation for parameter tuning and model selection for prediction problems. Now, is there a standard or if not a less-known way to measure the sensitivity of the parameters ...
68 views

### How does predictive model for the Eurovision Song Contest work?

I've encountered interesting prediction of Eurovision Song Contest http://mewo2.com/nerdery/2013/05/12/eurovision-2013-first-predictions/ it based on some kind of Bayesian model I assume but I don't ...
27 views

### Predict binary occupancy vector from history of vectors

I have a set of binary vectors where each vector represents one day of occupancy in a house and consists of 48 elements (each element for 30 minutes of the day). Each element can be 1 meaning that ...
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### Modelling rainfall to size storage tanks

I have daily rainfall data for a given site going back about 30 years. I have a building with an average daily demand for water of $L$ litres and a catchment of $A$ m$^2$ with a runoff coefficient of ...
113 views

### Faster alternative to multivariate LOESS?

I want to make predictions by creating a smooth response surface to 2 variables. I get good results using R's loess() function, but with 10 million observations, it is far too slow. Are there any ...
119 views

### Predicting percent of male and female party attendees

Problem #1: easy, probably solved Suppose someone holds a party (A) and invites $n_A$ people. You're not attending a party, but you get full list of guests' identity card and are told that out of ...
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### What is the relationship between 10-fold CV RMSE and test set RMSE score?

In my opinion, these two RMSEs are proportion related. I use the training set to get 10-fold CV RMSE and get a model on the whole training set to predict on the test set. As the training set is larger ...
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### Comparing predictive validity of separate IVs on single DV

I'm attempting to understand some data and would greatly appreciate help in picking the appropriate analysis measure. Context: I am conducting psychometric analysis of the predictive validity of ...
41 views

### Predicting user selections based on similar user

Lets say you give a set of users a set of polls, or give them a choice of foods to eat, or let them listen to a group of songs (guess like pandora). So looking at the choices that all the users make ...
240 views

### Implication / Interpretation of long term equilibrium VECM

I want to test the influence of exchange rates on a price index and struggle with the interpretations. My variables are I(1) First, I ran an OLS on first differenced variables which indicated a ...
145 views

### Support vector machines and Granger causality

I was wondering if Granger causality would be an efficient tool for searching for relevant input data for an SVM system. For example if I want to forecast SP 500 returns, I could put in my input data ...
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### How to build a predictive model using sound (frequency and amplitude) as the input

I'm working on a medical research project where we're looking at the changing resonances in femur bones during hip replacement operations. Some surgeons use the increasing pitch of the bone resonance ...
159 views

### Which probabilites are to be supplied to rcorr.cens and improveProb in package Hmisc?

Both functions are great for comparing, for example, survival models. The first especially for computing Harrell's C-index, the second for NRI and IDI. However, it looks like ...
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### Analysing choices pattern

we have a process in which, at each step, a set of elements are presented to user, the user choses one, his choice is recorded and next round starts with a new set of elements. For example: 1. ...
254 views

### Parametric or non-parametric tests? … or transformation?

I am using R to examine the relationship between two variables in a small data set (n=16). My problem is that I'm not really sure how to handle the analysis (read: I'm in deeper waters than I've ...
70 views

### Cyclostationary time series

http://en.wikipedia.org/wiki/Cyclostationary_process What are the methods in modelling and forecasting such time series? It is mentioned in the link above that there is a deterministic approach to ...
103 views

### Non-linear (e.g. RBF kernel) SVM with SCAD penalties implementation

Is there one? I think there's a penalizedSVM package in R but it looks to use a linear kernel. Can't quite tell from the documentation. If it's linear, is there a R package that lets me calculate the ...
404 views

### Cross validation procedure - is this right?

Just want to check that I am performing my cross validation procedures right. I'm using a non-linear svm. I do a five fold cross validation (5 splits of test/train on my original training data) and ...
2k views

### Does anyone have experience with IBM's “SPSS Modeler”?

SPSS Modeler seems like a great tool for data mining (especially for prediction etc.) but it is extremely costly for individuals like me (around 20,000 euros excl. tax). There is also a video. I am ...
89 views

### Predictive model for network data

Assume a network as a set of data, which are defined by their coordination $(x,y,z)$ and a weight on its edge. Now this data can be used as an input data to predict a single value. In my case, ...
231 views

### Understanding the Pareto distribution as applied to wealth

The Pareto distribution can be used to give a pdf for the wealth of a person chosen randomly from a population. (In fact, this was its origin. See, for instance, ...
31 views

### rain cloud radar image prediction

I have a small pet project, which evolves around predicting a radar image of rain clouds given past radar images... My data comes from the radar images on following site: ...
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### Warranty claims count prediction

I have weekly data of number of warranty claims from week of manufacturing. I want to use this historical data and predict the number of claims that may arise in next few weeks. I have read about ...
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### Forecasting time-series ahead by multiple time horizons

Suppose that I have daily data on the population of a small village, given by $Y(t)$, as well as daily data on various factors that are relevant to the size of the population in the future, given by ...
22 views

### How do I predict a person's rank given a set of characteristics?

I'd like to predict a person's rank on a list (1 being top ranked, 50 is last -- ties are allowed, i.e., two people can occupy the #2 rank) given a set of characteristics (e.g., age, occupation, ...
25 views

### How does gbm determine the missing node if the training set is complete?

I have a training set which is complete - no missing values, but yet if I pretty print one of the trees in gbm I see that the algorithm has determined a strategy for missing data. This is smarter ...
66 views

### whether to rescale indicator / binary / dummy predictors for LASSO

For the LASSO (and other model selecting procedures) it is crucial to rescale the predictors. The general recommendation I follow is simply to use a 0 mean, 1 standard deviation normalization for ...
47 views

### When to use weight of evidence in a predictive model?

Suppose I am building a binary logistic regression model with around 400 variables then how weight of evidence(WOE) can be used in here? Also, I have known that WOE is helpful in dimension reduction ...
89 views

### Predicting ecommerce variables based on visitation data - R or Python

I have 1.5 years worth of e-commerce data (orders and revenue) for 2 countries (US and UK) with daily metrics for visits, unique visitors, and page views. I would like to model these transactions and ...