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

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problems in doing logistic regression with unbalanced sample, give me some references

I have a dataset with lots Y=0 and few Y=1. I have to run logistic regression, so I'm using a retrospective sample in order to get a more balanced sample. Could someone give me some references that ...
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13 views

Prediction model on hybrid data

I am currently working with a data set where I have both continuous, discrete and categorical (without any order) data. And I have to predict a continuous data. To be concrete, my problem is a ...
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19 views

How to use prior information about likelihood of related observations in classifier?

I am building a classifier about a certain kind of observation (in this case I'm using SVM but the question can be applied to any other classifier). My observations occur in related pairs, where the ...
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26 views

Stata vs. R survival differences; weibull scale is different, problems predicting manually

I am trying to do some survival analysis in R and as a starting point, I want to make sure I can replicate a previous analysis. I notice differences and I will demonstrate them here. I feel like there ...
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1answer
57 views

What is “Prediction Accuracy (AUC)”, and how is it the number conducted in Machine Learning?

Here is the link in question: http://applymagicsauce.com/documentation.html When the Cambridge University Psychometric Center's "Apply Magic Sauce" defines how their ...
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1answer
30 views

How could the predictive mean in a GP become negative when both the prior and the training target values are non-negative?

I am training a Gaussian process regression where the training target values are between 0 and 1 and the prior mean is the fixed zero function. The predictive mean sometimes becomes negative e.g. ...
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1answer
80 views

Regression results have unexpected upper bound

I try to predict a balance score and tried several different regression methods. One thing I noticed is that the predicted values seem to have some kind of upper bound. That is, the actual balance is ...
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19 views

Predicted Probabilities changing in non-linear way

As you can hopefully see from my code, I am trying to create profiles for prediction against a dependent variable of Voting which is yes or No binary. As you can see, the only thing I have allowed to ...
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1answer
24 views

Prediction vs. Classification in neural networks

I am learning the backpropagtion algorithm, and would like to clarify some concepts. Suppose my training data set consists of 20-dimensional bit strings that are classified into 5 different classes. ...
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30 views

Best approach to predict significant factors without any complete cases

I have a dataset that contains records of donors with various biographical info (city, state, zip, number of children) and the total amount they donated over 10 years. Some never donated and thus the ...
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0answers
5 views

Penalize a long-form panel linear regression prediction?

What is the recommended penalty, if any, for a long-form panel when calculating multiple linear regression $\hat\beta$ parameters or predicting single responses from (unobserved) values of $X_i$ in ...
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1answer
53 views

Explain “validation” process of repeated k-fold cross-validation?

My understanding is currently that the canonical repeated k-fold cross-validation (CV) process might do the following if $n=100$ observations in sample, $k=5$ folds, $i= 10$ iterations (see iteration ...
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43 views

Model averaging predictions from lmer models

I am trying to model average predictions (not betas) and estimate confidence intervals from linear mixed models run with lme4::lmer. I have experimented with functions in the MuMIn and AICcmodavg ...
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1answer
15 views

Estimate linear regression paramaters with chain modeling for longitudinal data?

Within a frequentist, deterministic paradigm of multiple linear regression, is there a (standard) method to accomplish "chain modeling for panel data" in a way that avoids formal identity (and/or ...
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0answers
50 views

Suitable graph to compare predicted and actual values across multiple sites

I would like to make a graph to compare predictions with actual values. The graph must be independent of scale and show equal emphasis for over and under prediction. The purpose is to summarise ...
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0answers
8 views

How do i get prediction accuracy when testing unknown data on a saved model in Scikit-Learn?

i have a model i have trained for binary classification, i now want to use it to predict unknown class elements. ...
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1answer
30 views

R: Comparing predictive power

I would like to compare predictive power of large number of models- +/- 50. I itended to use the ttrTests package and SPA, but I was not able to install that one since it was removed from CRAN. ...
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1answer
22 views

Understanding Model Credibility with True/False Positive/Negative

I am currently going through a tutorial with regards to a evaluation for a Logistic Regression Model in regards to Bike Buyers (Microsoft Azure) For the scored Model the True/False Positive/Negative ...
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4 views

Comparison of two entities based on samples

Suppose I have two sample sets $X = [[x_1, y_1], [x_2, y_2], ...]$ and $Y = [[x_1, y_1], [x_2, y_2], ...]$ data set $x$ points may not the same, also y values change wrt other factors/parameters lets ...
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18 views

Can auto-predicted values ever improve linear regression?

You want to predict values of $y$ using a linear model of the following form: $ y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_3$ $y$ is significantly dependent upon all three variables. ...
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7 views

Predict function error for probabilities in glmnet? [migrated]

I am trying to predict probabilities in a dataset using glmnet. My code reads: ...
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15 views

On the prediction mean square error of a model

Suppose my model is $y_t = \alpha + \beta t + \epsilon_t$ the l-step-ahead prediction is given by $\hat{y}_{T+l | T} = a + b(T + l)$ where $a$ and $b$ are the OLS estimators of $\alpha$ and $\beta$. ...
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1answer
50 views

making predictions with log-log regression model

Is it necessary to exponentiate the predicted values in a log-log regression model? For example my model is: $\log(y) = \log(x)$ $\log(y) = -0.5141 + 0.5377 \log(x)$ if I wanted to make a ...
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5 views

Confidence interpretation from false negative rate

For my research I'm using a tool called seeSUMO, which predicts sumoylation sites in a protein based on sequence features. When it reports your results, it gives you a level of confidence for each ...
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34 views

How to prove that Innovations in the Innovation Algorithm are uncorrelated?

I tried to search on the internet but could not find a proof... For the innovation algorithm, I am refering to the one used in the time series analysis to predict unknow value.
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13 views

Technical Indicators reference [migrated]

I have been looking for a good reference where I can find how technical indicators of stock market analysis are calculated. I have a dataset (time series) which I want to extract these indicators to ...
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1answer
19 views

I was expecting 0 and 1 as an answer of a predict function in r

I'm doing a binomial family with method="glm" in train function (caret package) and as result I'm getting predicted numbers like "0.62325028 0.51807017 0.67119878 ..." and I was expecting vector ...
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1answer
40 views

Diebold-Mariano test for predictive accuracy

I am using the Diebold-Mariano test in the forecast package of R to test the predictive accuracy. In particular, I want to ...
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7 views

Using different sets of binary indicators based on another indicator - R, linear regression

I'm trying to come up with a prediction model for an output based on the hour of the day. I already have a simple model that predicts the output based on 23 factors that represent each hour of the day ...
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2answers
55 views

Predictive Accuracy formula in Excel or R [duplicate]

I have posted this question, not sure how to move that question to this stats.stackexchange.com. ...
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153 views

logistic regression prediction: changing interpretation with changing prior

The data include 3 equally sized subsets A, B and C, belonging to two classes: A belongs to class 1. B and C belong to class 2. The prior probabilities of an observation coming from class 1 ...
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12 views

Binary outcome and correlated predictors

I have binary outcome variable (infection yes/no), two types of predictors, correlated (CRP 1, CRP 2 and CRP 3) which can be numeric or binary (it's pretty same to me) and uncorrelated predictors ...
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1answer
16 views

Predicting Arrival/Departure of butterflies

I don't have a solid background in statistics. I am double checking with you on a phenomenon I am trying to study. we are doing a study of some very rare species of flowers. We are putting them in ...
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3answers
38 views

How to predict categorical reponse?

I am trying to predict categorical response by using several categorical variables and quantitative variables? I tried linear regression model in R, but I don't think it works well as the response is ...
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1answer
56 views

How multicolinearity affect the prediction

In a linear regression model, if some of the predictors are correlated, then in the output of most software, you will see very large p-value in those coefficients and very high standard error. My ...
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0answers
19 views

Prediction with plm method

I'm using plm package to estimate a random effects model on panel data. Reading this question about the prediction in plm package gives me some doubts. How exactly it works? I tried 3 alternatives ...
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38 views

A bunch of different types of variables (their combination also important) explaining one variable - which method?

I have a dependent variable - how much land does a household cultivate out of total in their possession. The answers are categorized in 3 different groups (1 - 70% - 100%, 2 - 40 - 70%, 3 - less than ...
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0answers
55 views

Elastic/ridge/lasso analysis, what then?

I'm getting really interested in the elastic net procedure for predictor shrinkage/selection. It seems very powerful. But from the scientific point of view I don't know well what to do once I got the ...
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26 views

Robust Measures for Forecast Accuracy

I am doing a forecast using robust exponential smoothing methods and to determine / measure the forecast accuracy I want to use robust measurements as well. As I am not really familiar with robust ...
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1answer
115 views

RMSEP vs RMSECV vs RMSEC vs RMSEE

I am getting real confused now, What is the difference between, RMSEP (Root Mean Square Error of Prediction), RMSECV(Root Mean Square Error of Cross Validation), RMSEC (Root Mean Square of ...
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1answer
11 views

Can a 1-D risk score (binary outcome) be sensibly used to create more than 2 treatment groups?

This question concerns predicted probabilities of a binary outcome, and the (I believe) misguided practice of making multiple cutpoints along a one-dimensional risk continuum -- cutpoints that create ...
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17 views

predict score model

I took modelling class and did some simply prediction on buy or not buy model and worked ok. Now I have a new project that I am confused about. I need to have score for a set of keywords, the ...
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30 views

predict sales using naive bayes and handle sparse data problem

Problem I am trying to use naive bayes for ranking products in a search application. I would like to predict the sales of a given product given the search keyword and the category. the current formula ...
2
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1answer
31 views

How can permutation test be used for assessing the prediction capability of a model?

I have a set of real labels $(y_1, y_2, ...,y_n)$ and predictions $(\hat{y}_1, \hat{y}_2, ...,\hat{y}_n)$ produced by my model. My supervisor has told me to assess the significance of the predictions ...
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1answer
42 views

Which one to compromise between MAPE and Adj R square in multiple regression

I'm trying to forecast sales of a product based on the other variables like Competitor sales, Fuel Price and CPI (Consumer Price Index). The below given output (based on 1 to 44 months) gives me the ...
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44 views

How to deal with separation in logistic regression in Stata?

I'm running a binary logistic regression on 15 independent variables for 180 observations in Stata (version 11). This I do for four different groups, i.e. four dependent variables. For three, it works ...
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1answer
47 views

how does a linear svm classifer work

I have been checking about SVMs in particular linear SVMs throughout many questions here. However, one problem i faced is that there seems to be no indepth explanation on how does linear SVM works in ...
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1answer
52 views

Extrapolating the effect of covariable changes in Cox proportional hazards models

I have a Cox proportional hazards model in R (see made-up example below) that models the effect of some variable, say weight. From this model, I'd like to extrapolate what a change in weight from say ...
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15 views

Applying isotonic regression calibration (using PAV) to new model predictions

I'm working on classifying models for a few different projects. Several papers on the subject of calibration all suggest using isotonic regression (using PAV) to adjust the model probabilities. I ...
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33 views

BayesA, BayesB, etc

I would like to get a plain English explanation of BayesA, BayesB. I found that a lot in bioinformatic literature but found nothing in Wikipedia, etc.