Prediction is concerned with assessing the probability of unknown values from known values and inferred relationships.

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How to prove the reliability of a predictive model to executives?

I trained data from 500 devices to predict their performance. Then I applied my trained model to a test data set for another 500 devices and show pretty good prediction results. Now my executives want ...
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17 views

Confidence and Prediction Intervals for Multiple Linear Regression Model

I am looking for a derivation of confidence and prediction intervals for a multiple linear regression model. I have seen that for a given vector of predictors $(x^*)$ and $X$ denoting the design ...
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8 views

Predictive inference of interval sampling for proportions?

Suppose I am sampling periodically (each month) over a year a substance that is degrading over time. The process of sampling is destructive so I am using difference samples each month. At the end of ...
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1answer
26 views

Is it possible to add up the accuracy rates of 2 predictors?

Weather channel 1 has a 65% accuracy rate of predicting tomorrows weather Weather channel 2 has a 59% accuracy rate of predicting tomorrows weather Is it somehow possible to take into account ...
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27 views

Bayesian prediction for unobserved sampling

I have the following bayesian ZIP model: ...
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2answers
90 views

Is test MSE all that matters when it comes to prediction?

I'm wondering if when it comes to predictive analytics, whether a lower test MSE is really all that matters. Should I not even look at residuals - other model diagnostics when it comes to prediction ...
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15 views

Time series with slightly unequal intervals

I'm very new to statistics, and I have a problem that may or may not exactly be considered a time series analysis problem. I have a large set of vehicle location measurements (x0, y0)...(xt, yt) taken ...
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10 views

Binary outcomes with low goodness of fit (GOF) but good predictive power?

We know that it is possible that a model predicts the outcome reasonably well (and hence high R-square) but is actually misspecified (and hence low goodness of fit), as this example shows. The ...
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6 views

Which will be better If I have 2 years data (training and testing) with a condition

Condition: I will always asks the model to predict the behavior of last 1 month data i.e I want the result on last 1 month of data. I have 2 years of data of my app, and I have to train the model and ...
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25 views

How can I decide weight in negative binomial regression?

I'm on my project to predict the amount of demand of products in a store. we have lot of 0 on the amount of sales of products so when I did multiple regression, predictions of the demand had negative ...
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3answers
32 views

how to predict sales of an item changes based on a discount given to another item?

I am developing a system where the management of the supermarket can make decisions on past sales data. There I mainly want to focus on how to predict sales of an item changes based on a discount ...
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1answer
56 views

Reverse Engineering using machine learning

First I want to say I'm completely new to the machine learning paradigm and have only discussed it in theory. I have been trying to put it into practice but I'm confused on how to derive the dataset ...
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12 views

Marginalized Denoising Autoencoder for Regression/Prediction

I have been looking online at papers etc. about marginalized denoising autoencoders (mda) and everything I've found so far uses mda for pre-training layers for a classifier such as a support vector ...
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1answer
46 views

Prediction Model on categorical y with more than 20 levels

My goal is to predict y, but my dependent variable y has more than 20 levels. I dont think multi-nomial model would be a good ...
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0answers
29 views

Effect of covariates that have been removed from a model

I am fitting a GAM to data of capture success in trapping sites using the mgcv package in R. The independent variables are proportions of land cover types. Here is the output of my model: ...
2
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1answer
31 views

How to perform predictions using a probabilistic model?

Suppose that we have fitted a probabilistic model (like GLM) to the data in order to perform predictions using test samples. The question is how to perform such predictions having the conditional ...
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1answer
74 views

Hurdle model results interpretation and plotting

I am trying to determine the habitat of a species of dolphin. My data is highly zero-inflated, so I chose hurdle and zero-inflated negative binomial models to analyze it. I used the pscl package in R ...
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0answers
14 views

Building a prediction raster when the statistical model was built from sampling units of different sizes

I would like to build a predictive map of capture success from a GAM. To build the GAM, I used data of capture success (dependent variable in the model) and proportions of land cover types (...
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6answers
1k views

Variable selection for predictive modeling really needed in 2016?

This question has been asked on CV some yrs ago, it seems worth a repost in light of 1) order of magnitude better computing technology (e.g. parallel computing, HPC etc) and 2) newer techniques, e.g. [...
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1answer
27 views

how to classify short text sentences?

I have a very large dataset that looks like string x this-is-a-nice-sentence 1 hello-my-name-bird 0 yay-this-is-awesome 1 ...
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1answer
23 views

Prediction of vertex scores in a bipartite graphs

I have a bipartite graph with two sets, A and M, of nodes. Every vertex in M has a score associated with it. I have two tasks: To every vertex a in A, I have to assign a score based on the scores of ...
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8 views

How to deal with continuous variables with NULL values in prediction tasks?

I'm currently working on a machine learning project, trying to predict the expected revenue from a specific user. I have a long list of features that display the date when the user first performed a ...
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1answer
26 views

How best to summarize a predictive discrete distribution in a single number?

I have generated a predictive distribution for a future discrete observable outcome, and would like to generate a single value $p$ which we would most likely encounter when we perform the experiment ...
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1answer
25 views

Standardization and prediction on new data

As far as I know it is common practice to do standardization of variables before shrinkage or PCA, which are methods I intend to use on my model selection for a predictive model. But the problem is, ...
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0answers
15 views

how to do Grade prediction by previous score

My scenario is as follow: I got several years ago of my students score of school exam result and their public exam result. And I have a box-plot of the school exam score to public exam grade. I got ...
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1answer
28 views

Compute likelihood of two events happening at the same millisecond [closed]

I would like to write a python (or R, etc) function that computes the likelihood of two events happening at the same millisecond. The events are independent an can happen at any time of the day. My ...
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1answer
17 views

The prediction at the average of the covariates is different from the average of the predictions

I read in Stata manual : "The prediction at the average of the covariates is different from the average of the predictions" after a logistic regression. If I compute predictions for a linear ...
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21 views

Shapley Value Regression for prediction

I've been successful in using the relaimpo-Package for R in SPSS through STATS_RELIMP to calculate the Importances of different predictors (in cases of multicollinearity). What im wondering now is how ...
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1answer
56 views

Low performance of SVM (and neural network) in out-of-sample data with high test accuracy of 10-fold cross validation in a financial time series

I'm using SVM and (neural network) for a time series prediction data-set in MATLAB R2016a with 800 samples. Currently I'm using 10-fold cross validation and grid search to find best SVM parameters. I'...
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10 views

What is the best way to predict communications in a large social network?

I need to make a recommendation system that would predict friends for users in the social graph. The number of users is around 1.500.000. I thought of creating all possible pairs of users and then ...
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9 views

what is the difference of prediction model in high dimensional setting and multivariate setting?

I am wondering what is the difference of prediction model in high dimensional setting and multivariate setting. Do the difference just lie in that we need to make dimension reduction for high ...
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1answer
29 views

How does the forecast package compute prediction intervals?

I'm currently working with random walks with drift in R, I use the rwf formula from the forecast package and I wonder how the prediction intervals are computed. As I understand it, for the random walk ...
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1answer
61 views

Prediction of independent data with PLS

In Matlab's plsregress function and in many other statistic toolboxes, there is a BETA vector returned that simplyfies the regression problem to(excluding the ...
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1answer
177 views

Adjust VS Predict on Stata

I'm trying to obtain predicted values after a linear regression with Stata. However I don't find what the command Predict does with the covariates. I think that the command Adjust holds their values ...
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12 views

Create clusters of higher probabilty from binary data

Good evening, I've been asked to prove that there are groups of customers who have reacted to a price increase differently, specifically do some groups have a higher probability of cancelling their ...
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35 views

Using predict.rma with categorical and continuous moderators

I am trying to use predict.rmawith one categorical SNACK and one continuous CALORIES ...
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21 views

Predicting a parameter using the estimates of a series of studies, using study location and year as random effects

I would like to ask whether my analysis design is correct. I gathered all the trials on a series of drugs for a certain condition (second line therapy for advanced/metastatic lung cancer), published ...
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1answer
20 views

model to predict variable evolution

Suppose that I have a set of variables X1 X2 and X3 that explain the evolution of a ...
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1answer
14 views

First order model vs n-order models

Plenty of different research models showed that n-order models give better results than first order models. For example, for location this is work that shows this http://dl.acm.org/citation.cfm?id=...
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24 views

Predicting occurrence of an event using time series data

I have data coming from sensors for 1 month. The data is time series with each data point separated by interval of 1 second. There are predictors like temperature, pressure, speed of the fan that has ...
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27 views

How to predict when using normalized data?

So, I am taking this course on machine learning by Andrew Ng. Wanted to write my own linear regression program. Everything is fine. I mean normalize data, and run linear regression. Now I'm left with ...
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24 views

How to create training set for uni-variate prediction using SVM?

I am new to R and statistics. I have a problem related to the prediction: I want to predict a univariate time series using SVM, but I do not know how to construct the training set. what I want is that ...
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11 views

Strange predictions from binomial glmm?

I am analysing the dominance of a Species, i.e. its relative abundance in a community. Since these data are proportions I use binomial models. However, the predictions from these models are ...
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1answer
47 views

Optimal Cutpoint for Predicted Results from Kaplan Meier and Cox Regression

Is there anyway to get the optimal cutpoint for predicted survival probabilities of the aforementioned survival analysis approaches? Something like the optimal cutpoint from ...
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0answers
11 views

adjusting nnet model for prediction

Could someone give some hints how to adjust paramters in nnet model for predictions ? I mean following parameters: maxit, range, decay, size, and ...
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0answers
24 views

Using predict() to plot glm (and glmm) with continuous and categorical explanatory variables

I want to visualize the output from my glm by plotting the predicted values, and found an example in the Mixed Effects Models book by Zuur (pg 216-219). The description of this code from the book is: "...
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0answers
68 views

Is it possible to do a time series analysis with more than one explanatory variable?

I am working on a project, and I am absolutely new to forecasting and not so strong in statistics. I have an employee data for the last 7 years, along with the other variables like economic growth, ...
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1answer
14 views

validate correctness of prediction

I have two datasets. 1st contains original data. 2nd contains predicted data. I want to count how well the prediction was. I was assuming following algorithm: Calculate absolute difference between ...
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14 views

Polynomial curve fitting for temperature prediction

First of all, I would like to say that I know very little about statistics. I need to make a C# application to predict three days weather for school project and need some model and have been exploring ...