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

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Help logistic regression [on hold]

I have to predict a binary variable with logistic regression. The idea is to classify a number of subjects each either sick or not sick. Therefore, I have 11 risk factories for each person and have to ...
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12 views

What is the final equation used to produce new prediction using kknn on R

I have trained my data using kknn on R and was able to predict on a new data set. However, I'd like to know what the actual final equation is so I can reproduce the prediction manually. My training ...
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29 views

Markov models that with several active states

Are there any Markov-like models that can have several active states? So say if trying to determine (the chance) when the person will wake up based on two variables (weather and the time the person ...
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22 views

what is the size of data should be predicted to make the predictive model valid

if I have time series with 1000 values , and I want to build a predictive model , how far in the future should i successfully forecast to make my predictive model valid, is there any condition or rule ...
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12 views

How to compare models using bootstrap optimism adjusted prediction error?

Let's say I'm comparing the prediction error of two different models. For illustration purposes we'll use a toy example. I've generated 5 bootstrap samples and fit Model A and Model B to each ...
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14 views

classification, discrimination, prediction, clustering

note: i am restricted to using SAS in this project, no R).The purpose of my problem is to predict the response variable. to start off, I have a large dataset (medical study on diabetes prevention) ...
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1answer
33 views

Neural Networks and Numeric Prediction

I'm new to machine learning and am trying to write a simple neural network that uses back-propagation. Now, so far I've successfully implemented my neural network to learn a boolean function. So for ...
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15 views

Combine several days of time series into one

I have twenty time series from twenty days. Can I concatenate these time series into one, and run a simple linear regression on the resultant series?
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2answers
44 views

Can a simple linear regression be applied to a time series with non-constant time interval between observations?

I have a strictly ordered series of observations where the time between the observation is not constant. I am wondering if I can apply a simple linear regression on this and treat it as I would treat ...
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18 views

How far can we predict in time series of price index?

If I build a model for time series that represents the price index of a stock market for 5 years, how far can I predict in the future? The reason for this question is that I want to be sure that the ...
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5 views

Evaluate and report fit of a model on validation cohort(s)

I trained a random forest regression model M on a training set. I am interested in how well the model predicts the responses in 3 different validation sets. I am also interested in the characteristics ...
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4 views

Test statistics for MAPE

I am working with longitudinal panel data where I use variables of the first panel wave as training data in a regression to predict the consecutive waves. To compare different prediction approaches I ...
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1answer
12 views

Dummy variables and intercept in Cox regression

I am working with the Cox Proportional Hazards model. Where the covariates include 2 categorical variables. Assume each category has 3 levels, so I model these in terms of dummy variables. Category ...
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1answer
51 views

Using predict() in R to predict the y-value for multiple occurrences of the same x-value

If I have a linear model and want to use predict() to predict the mean and confidence interval of multiple ($m$) new observations of a given x-value ($x_h$), how do ...
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1answer
22 views

Best way to combine information from different models

I have 3 models using different methods for the same outcome and predictor variables of a training set. I can apply these models to a new test dataset for predicting outcome variable. Is it a good ...
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1answer
28 views

Data Projection in the Future

Suppose we have the following data: ...
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31 views

Restricting a set of predictions to a range of values of non-negative numbers

I am not even sure how to even phrase this question so if anyone could help that would be great. I am analyzing facebook activity and I wish to predict a particular activity (comments, for instance). ...
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30 views

Rolling window forecasts in Python

I asked this question some days ago but haven't got any response. So I've taken it to myself to do the rolling window manually. My limited grasp on regression forecasting has stumped my progress a ...
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0answers
16 views

Strange predict() results from GLMMadmb after adding Zero Inflation

I am attempting to model abundance of a species based location groups and environmental parameters. I've encountered a problem with the predicted values from these models that is associated with ...
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36 views

Rolling volatility estimation using GARCH family of models in python

Problem: Correct usage of GARCH(1,1) Aim of research: Forecasting volatility/variance. Tools used: Python 3.3 with arch library I am trying to obtain out-of-sample estimation of volatility using a ...
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1answer
31 views

How to calculate $\phi$ (phi) - a first order autocorrelation coefficient

I have a dataset of historical quarterly earnings per share for 8 years. I am trying to use the following formula for the purpose of estimating earnings: $E(Q_t) =Q_{t-4} + \phi_1(Q_{t-1} - Q_{t-5}) ...
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32 views

Can I have only one observation for each combination of factor levels in a regression model / is this model appropriate?

Can I have only one observation for each combination of factor levels in a regression model, or is this model appropriate? I have what I thought was a simple problem. I am working on a problem ...
2
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2answers
76 views

How to reduce error rate of Random Forest in R?

I want to build a prediction model on a dataset with ~1.6M rows and with the following structure: And here is my code to make a random forest out of it: ...
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2answers
18 views

Prediction of n class variables

I have a historical data that has discrete variables. Let say I have data points with class labels 1, 2,3,4,5. For a given classification problem, I can use the training data and then get the trained ...
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1answer
62 views

Random forest and model predictions

I have a working random forest model (classification tree) in R that I made with a training dataset. I used the predict function with a verification dataset: ...
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8 views

Predicting individual treatment effects as the difference between predicted outcomes with and without treatment

To provide some context, I am trying to (a) identify the best ad to increase support for a particular issue among a large group of people, and (b) identify the people most likely to respond positively ...
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1answer
24 views

Forecasting model - Scale mismatch

I have the following data: As you can see I want to create a regression model, which forecasts a variable, which I have also on a quartely basis. However, my volume is only on yearly basis. Is ...
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1answer
38 views

Random forest regression prediction for high dimensional data

I am working on a project by using a high dimensional data set. Close to 50000 Obs. with 392 Variable. I used lasso to reduce it to this point from a total of 1200 variables. And the whole data set ...
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2 views

Adjusted prediction (marginal effects) and implications on analysis

I have been reading about adjusted prediction (also termed marginal effects) e.g. https://www3.nd.edu/~rwilliam/stats/Margins01.pdf and have been pondering about the implications on, for instance what ...
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33 views

Alternatives to Google Prediction API?

The Google Prediction API seems like a great machine learning product because it is generic (works with any type of machine learning problem), and is very easy to use with a simple API. Unfortunately, ...
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1answer
36 views

Classification trees: the best Predictor and the ability to predict

The topmost decision node, the root node in a classification tree is said to be the best predictor of the model. Does this mean the root node variable is also the best in predicting the target ...
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2answers
43 views

statistical prediction [closed]

I am new to statistical methods so this question may be very simple for you. I want to know some "statistical prediction methods" for a sequence of numbers. The numbers may represent financial or ...
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1answer
34 views

Prediction based on bayesian model

I have created a bayesian model that estimates 6 parameters using rjags from R. Now i want to do some predictions based on new data in R. Can anyone help me with an example. ...
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1answer
49 views

More Statistical Way to Average N Predictions

I've run a RandomForestRegressor (Scikit Ensemble) over N loops, each time changing the random seed and therefore changing the train test split. This way I've N sets of predictions (M predictions for ...
6
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1answer
153 views

Prediction interval for lmer() mixed effects model in R

I want to get a prediction interval around a prediction from a lmer() model. I have found some discussion about this: ...
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22 views

Why the prediction of multivariate GARCH is just a line?

I'm doing multivariate GARCH analysis between two stocks, like many examples you can find online. The fitting goes very well but I'm confused by the prediction part. Why the forecasted conditional ...
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2answers
79 views

Test whether two predictions are significantly different

I am currently stuck with a problem regarding predictions from linear regressions. I estimated a simple (multivariate) regression model y = b0 + b1 * x + b2 * X, where x is my variable of interest and ...
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27 views

Predicting attrition

I am trying to build a model which will predict attrition in an organization and will also find out the key drivers which leads to employee attrition. I am not looking at any special scenarios too. I ...
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1answer
18 views

Using Diebold-Mariano test to compare predictive errors in non-time-series?

I understand that the DM test is established for time series data, but could I still apply the test for non-time-series data? Could I simply replace the autocorvaiance part of the test statistics with ...
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10 views

relationship between power means and population zscore calculations

Can one use a power mean of the ages in a room to determine the age break down of a room? Let's say you have a room full of people, by using the average age and standard deviation of the age, how do ...
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1answer
21 views

What is the difference between the standard errors calculated by predict.lm() and summary.lm()

I am trying to calculate standard errors of group means for a two-way-anova. I found two ways to do this (predict.lm(, se = T) and ...
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14 views

Technology Acceptance Models can be used for prediction?

I am planing to conduct a survey to predict the adoption of Mobile Banking service in the country where it was not introduced before. I am wondering whether it is possible to apply the Technology ...
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30 views

Prediction Interval for a Zero Inflated Model

I am not a statistician. So any help is appreciated. I am modeling the cost with many. The predictors are 2 categorical variables V1 and V2. The non-zero cost form a Gamma distribution. I considered a ...
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9 views

Updating model parameters online on test data

I learn the parameters of a temporal model (in my case, an RTRBM) on some training sequences using mini-batch gradient descent. Let's say now that I am updating my model online after every prediction ...
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16 views

implementation of Poisson regression [duplicate]

I am trying to work with Poisson regression. I came across this video which is very helpful - https://www.youtube.com/watch?v=HntUY8SsYZg. In the video one of parameters (Race) is categorical and ...
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14 views

How can I determine if there is a effect relation between variables if the cause is delayed with respect to the efect?

I have a dataset from a process in which one of the variables codifies an event that I want to explain using the rest of the dataset. The problem is that the relation of the variables with the event ...
4
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1answer
69 views

Evaluate posterior predictive distribution in Bayesian linear regression

I'm confused on how to evaluate the posterior predictive distribution for Bayesian linear regression, past the basic case described here on page 3, and copied below. $$ p(\tilde y \mid y) = \int ...
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1answer
30 views

How much prediction accuracy of SVM (or other ML models) depend on the way features are encoded?

Suppose that for a given ML problem, we have a feature which car the person possesses. We can encode this information in one of the following ways: Assign an id to each of the car. Make a column ...
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1answer
17 views

Techniques to deal with unobserved values in test [duplicate]

In my data, I have some items that a customers purchase. I need to predict the customers behavior with different items. But in the test set, there are some items that are not present in the training ...
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13 views

Estimating the opinion of a user by looking at opinions of other users

First of all, a bit of background: i am not a statistics expert but i am an enthusiast about data analysis. I have this list of "items" and for each item i have a list of "users" and the vote that ...