# Tagged Questions

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### How do I sample from the posterior predictive distribution of a Bayesian mixed effects logistic regression model?

Suppose I want to sample parameter values from the posterior predictive distribution of a generalized linear mixed effects model from the binomial family and a logit link, and I want to incorporate ...
55 views

### How to predict demand from historical “continuous” event data (date, lat, lon)?

I am attempting to predict demand for our service, both quantity but maybe more important, location (hotspots). I am by no means an experienced statistician, so I need some help :) I have all the ...
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### Perfect sampling from a huge dataset

I am working with a binary predictive model for data that belongs to A and B. The learning sample that I am using contains 6000 row that belongs to group A and 1000 row that belongs to group B. I ...
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### Plot prediction for covariates from GLM

I have run GLMs and got my final model that fits my data. Now I would like to plot each of my important covariate versus the predicted values. I would like to keep all the other covariates of the ...
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### Predicted Responses as Weighted Averages: Classical Regression Vs. Mixed Effect Models

Let's imagine that I have collected data in a longitudinal design that would lend itself to a mixed effects analysis. So suppose I perform a research study with human subjects and observe responses ...
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### Measuring prediction quality given discrete predictions of a continuous dependent variable

Say we have a variable that can assume all values between 0 and 1 and we have a system that predicts measurements of this variable providing estimates in terms of 6 discrete levels (let's say 0, 0.2., ...
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### Unbiasedness condition in ordinary kriging and simple kriging

I have this confusion. In ordinary kriging we have used the unbiasedness condition which gave the sum of weights equal to one. However, in the case of simple kriging we have no such conditions why? I ...
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### Confidence with probability values

I am constructing a predictive model for a binary outcome, which gives me results in a "probability-prediction" fashion such as "0.3-YES" or "0.4-NO". The model is working perfectly. My question ...
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### Confusion matrix of random Forest doesnot match predicted probabilities on train data

Based on an earlier question I balanced the classes such that the numbers in both classes is about similar. The random Forest gives next result: ...
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### Ideal learning sample in machine learning

I am constructing a model for the prediction of a binary (Yes/No) outcome. I have a learning sample that gives the machine 1500 examples of the "Yes" group and 500 example of the "No" group. Should I ...
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### Prediction of a binary variable

I am establishing a model for prediction of a binary variable (Yes/No) depending on three continuous variables ($A$,$B$,$C$). I applied logistic regression analysis for a learning dataset vith the ...
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### Why can weather prediction be so correct?

I've done a test using ARMA model on some financial series. It turns out the prediction rate is really very bad – close to half time correct and half time wrong… I am new to ARMA model so what I ...
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### How to predict rank in ordinal regression using R?

I have done an ordinal regression using lrm from the rms package. ...
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### R neuralnet - compute give a constant answer

I'm trying to use R's neuralnet package (documentation here) for prediction. Here what I'm trying to do: ...
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### How do you predict probabilities for specific data in logistic regressions using R?

Consider the Challenger-Disaster: ...
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### Building reliable glmnet model and constructing predictions

I am new to glmnet. I have over 15,000 predictors and a binary outcome for approximately 400 samples. I am having trouble finding sources online to describe explicitly if what I am planning to do is ...
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### Cox proportional hazard lift gain charts

I have built a Cox PH model. I obtained the predicted survival probabilities. My questions are: How to get the predicted survival time, or time to event, using survival probabilities? I need ...
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### Prediction in support vector regression

Has anyone attempted prediction using support vector regression? I'm using LIBSVM, but I'm not sure how to use SVR in either univariate and multivariate time series. Say we have stock prices for $N$ ...
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### Predictive website analytics with irregular data points using R

I am trying to use R to build a time-series model to predict a variable which is only reported on irregular intervals. I have data for independent variables for all time periods (days), however the ...
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### Modelling zero-inflated proportion data in R using GAMLSS

I am new to the gamlss package and would like to check that I am using the correct family for proportion data (tree species cover after treatment), which is bounded ...
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### Obtaining predicted probabilities that include multiple random effects from mixed effects model

I'm running a mixed effects logit model with a binary response variable. The data are cross-national survey data, over multiple waves (i.e., World Values Survey). As such, the random effects specified ...
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### Repeating random forest models to get highest prediction accuracy

I am using a random forest code to run one random forest model and distinguish which variables are important for classification and then to run a second random forest model using only these variables ...
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### Can we calculate the standard error of prediction just based on simple linear regression output?

The standard error of prediction in simple linear regression is $\hat\sigma\sqrt{1/n+(x_j-\bar{x})^2/\Sigma{(x_i-\bar{x})^2}}$. My question is to calculate the standard error of prediction for ...
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### Interpretation of interaction term in Cox PH model when centering LP on mean values of predictors

Let's say I have a Cox PH model for predicting the risk of dying, that in a simplified form looks something like this: ...
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### Methods for time-series prediction depending on multiple parameters

We have hourly time-series data of the status of a system: number of people present at different train stations. We collected it for a year, and we want to use it to train a model to predict the ...
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### Count data forecasting/prediction

I would like to know if the normal forecasting methods apply for count data, in specific a dataset that contains several zeros? I have data set that counts the usage of a service on an hourly basis, ...
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### How do we use existing z-scores to predict actual z-scores in a large (16 million vector) data set?

We started with a set of 4,000 journals. These journals do or don't share certain qualities. We then created a vector between every journal A and every journal B. That gives me 4,000^2 or 16 million ...
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### Event Prediction through Machine Learning

I have a large data set consisting of ca. 40 categorical data items and a few interval data items (real numbers, less than 5 such items). Most categories should have a lot of values that repeat ...
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### Confused about independence and prediction power of data

What is the correct way (if there is one) to think about when authors claim that stocks have produced some percentage annual return X over every 20 year period of time? They might calculate this by ...
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### Prediction error and covariance penalty

I am studying the paper by Efron: The Estimation of Prediction Error: Covariance Penalties and Cross-Validation. To estimate prediction error in the Gaussian case by Mallows' $C_p$ or other methods ...
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### Finding temporal patterns that predict “life length”

I'm doing research on system usage. It is an online system that provide certain information to users, and I want to predict for how long users use the system. I already noticed that if people don't ...
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### Prediction using SVD and Fisher's linear discriminant

Where can I get an explanation of the procedure used when making a prediction using SVD? Let me elaborate a bit more. Suppose you have data in a matrix $A$ containing two classes. In particular, you ...
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### How would I go about analysing MMA statistics and data for future predictions?

My maths knowledge is pretty poor but I'm looking to improve on a new project I'm interested in. I have data from thousands of MMA fights/fighters including weights, height, reach etc. and I'm trying ...
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### Prediction with randomForest (R) and missing values

I have a fine randomForest classification model which I would like to use in an application that predicts the class of a new case. The new case has inevitably ...
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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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### Random forest algorithm

I have a question about Random Forest algorithm: 1.Let the number of training cases be N, and the number of variables in the classifier be M. 2.We are told the ...
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### Random forest and prediction

I am trying to understand how Random Forest works. I have a grasp about how trees are build but can not understand how Random Forest make predictions on out of bag sample. Could anyone give me a ...
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### Getting unbiased probability predictions from kernlab SVM

I am creating a meta-classifier that uses probability predictions from many base classifiers, among which I use SVM classifiers. It is a two-class prediction problem (outcomes are 'yes' or 'no'). I ...
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### How to algorithmically find plausible covariates at which to plot predicted responses?

I'm trying to plot the predictions of a linear model with multiple numeric predictors as a collection of plots such that $\hat Y$ is on the y-axis, each $X_j$ in turn is on the x-axis, and the ...
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### measuring the predictive power of a (linear) model

In a relatively simple setting, I try to fit a simple linear regression model. I want to assess how good this model for prediction. basically I try to do something like K-fold cross validation or ...
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### Sample size with respect to prediction in classification and regression

With respect to hypothesis testing, estimating samples sizes is done through power, and it is intuitive that increasing the same size increases the precision of estimated effects. But what about ...
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### Prediction of $X_{t+2}$ of an AR(2) process.

I want to find the best linear predictor, in MSE sense, of $\hat{X}_{t+2}$ in terms of $X_s'$s where $s \le t$ and $$X_t = \phi_1X_{t-1}+\phi_2X_{t-2} + Z_t\,,\, Z_t \sim WN(0,\sigma^2)$$ $X_t$ is ...
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### Reconstructing time series data with missing values from external data source

I have a 100 year time series. But the first 30 years are missing. So I correlated the 70 years that I have with another (100 year) time series to predict back / reconstruct the missing values. For ...
156 views

### What machine learning techniques can, once trained, generate prediction despite some missing inputs?

I have a training set where the inputs & outputs are all present, but I suspect that in the data where I want to do prediction, I will occasionally encounter scenarios where a small fraction of ...
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### Is there a statistical model for modelling variables that are measured in varying amounts and in different time points per individual?

I have been trying to model a dataset of variables where each individual is measured a different number of times, and at a different point in time. Most of my variables are counts, but some are not ...
51 views

### projecting future survival rate

I'm working on a customer retention project that predicts the probability a customer is still subscribing to our services at time T. Unfortunately, we only have the most recent two years of customer ...
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### Should the number of parameters depend on the purpose of the model?

I am curious what are some arguments for/against increasing/decreasing the number of parameters depending on the purpose on the model. I am currently building a model which will be used for ...
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### Why does increasing event weight in logistic regression increase c-statistic?

I have a logistic regression model that uses all events and a sample of non-events as the training and test population. The observation weights are chosen following King & Zeng. Events are ...