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

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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
496 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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8 views

Can I add categorical variables in NARX [on hold]

Can I add categorical variables as exogenous variables on NARX(in Matlab)? Eg: Type of day, Month
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1answer
17 views

how to classify short text sentences?

I have a very large dataset that looks like ...
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16 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
23 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
23 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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11 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
26 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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17 views

Predicted values in random intercepts model with more than one explanatory variable [closed]

I want to obtain predicted values from random intercepts model by setting some predictors constant. I have a data set of 58 countries. I ran a RI model after controlling for demographics (...
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1answer
13 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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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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47 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. ...
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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
25 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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49 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
58 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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10 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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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
12 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 ...
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13 views

Forecast package Prediction Horizon issue in R [migrated]

I am new to R. I was trying to predict using holt method but getting this strange error. I am using forecast package V-7.1 with R (version 3.2.5) and Rstudio (Version 0.99.896). I reinstall all from R ...
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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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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
42 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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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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19 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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64 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
12 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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10 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 ...
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55 views

Stata: Predicted values in autoregressive system

I'm trying to replicate the results from Yagan (2016, pp 8-11). There, the following autoregressive system is run: The author then runs this system based on data until 2007. Then, he computes ...
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questions about predicting time series using gaussian process regression

I am using gaussian process regression to predict a time series. The time series is number of daily active users(DAU) of an APP, and takes daily numbers of installing users and uninstalling users as ...
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13 views

How to use dummy variables for prediction

I have a sales data and in that data I have introduced dummy variables to capture the sales trend like "is the store open on sunday"."is the sale more that certain threshold" etc. Now if I train a ...
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1answer
58 views

Linear Regression Prediction vs Extrapolation Prediction

Suppose we observe $x$ and $y$ and we want to predict at $x=5$. A naive way would be to take each observation and compute $5/(x/y)$ or similarly $5*(y/x)$ and then take the overall mean. Thi is ...
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Predictions from Poisson GLMM (lme4) lower compared to GLM

I am modelling visitor counts to a sample of sites in a forest in order to predict the number of visitors to the rest of the forest. My predictor variables are time of day (categorical), day of week ...
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1answer
29 views

Forecasting survival probability using Cox Regression

I'm able to obtain predicted survival probabilities of cox regression using either survfit.coxph or predictSurvProb from ...
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19 views

least squares approximation to predict weather

I have daily temperature and rainfall data of fifteen years. I do not know much about stats. So here is my question. How do i use least squares approximation to predict temperature of at least three ...
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35 views

Bayesian networks - prediction question

Let's consider a dumb spam filter BN (see figure below) for which I've already calculated the a posteriori parameter distributions (see normalized table values). I want to predict if next email ...
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1answer
52 views

How to set the prediction range of ARIMA model in R

I am new to R and statistics. I have a problem related to the prediction: I am not able to plot the real value together with the predicted value. PROBLEM: I want to feed first 16 values into the ...
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UK population and NHS spending projections

Say I want to make some projection about the size of the UK population 25 years from now and consider the impact of this population growth on national health spending. Is the following approach ...
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27 views

Posterior Pred. Distribution for Bayesian Hierarchical Regression Model for Existing Group Parameters

For a hierarchical regression model, I understand that there are two posterior predictive distributions potentially of interest: (1): The distribution of future observations $\tilde{y}$ ...
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When making out-of-sample predictions, is there a reason to keep observed values for the predicted variable?

the dependent variable of my investment model has a large number of missing values. Fortunately a variable with a strong relation to the investment value is available for all observations, so that I ...
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19 views

Prediction interval for multi step forecast

I am using the "drift method" to make a multi-step forecast. The formula for the forecast is $y_T = \frac{h}{T-1} \sum (y_t - y_{t-1})$, where $h$ is the forecast horizon and $y_T$ is the last ...
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Predicting multivariate uneven time series of discrete/categorical data

I have a basic background in stats, DSP, ML etc. but by no means an expert so some of my terminology is going to be rusty. It probably makes the most sense if I simply show you what i wanted to do and ...