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

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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
20 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
36 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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119 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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9 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
15 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
33 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
53 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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13 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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35 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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42 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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21 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
38 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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0answers
15 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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22 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 ...
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1answer
28 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
31 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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36 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
42 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
41 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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9 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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31 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.
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Looking for application to help predict win/loss based on previous wins/loses

I play in a basketball league that has 8 teams in rotation. Scores are kept so wins/loses are recorded along with number of points for/against. They don't post the final game scores, just an aggregate ...
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46 views

Nate Silver's Election Prediction Model

Nate Silver has been quite successful at predicting the outcomes of U.S. elections in the past, something which is described in his book The Signal and the Noise. The book contains some descriptions ...
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1answer
122 views

Using canonical correlation analysis (CCA) to find matches

I have a training dataset of images: X (Visual) and Y (Infrared). Each set has $300$ training examples. I extract feature ...
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1answer
45 views

Forecasting in Stata

I am working with time series data and fitting an autoregressive model using OLS. For reference, here is my price data for the commodity (I am not sure how to better format data for this site): ...
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1answer
50 views

Are prediction and distribution-fitting ever not the same thing?

Intuitively, it seems to me that, if one is able to make accurate predictions about a variable, then one has also (perhaps implicitly) produced a good estimate of its marginal or conditional ...
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2answers
84 views

What criteria tell us that the prediction of a model is reliable

What criteria can be used to tell whether the prediction of a model will be more reliable than other specifications. Background: We have data with $N$ computers. However, prices available only ...
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2answers
43 views

Are cross-validated prediction errors i.i.d?

Say, we test an arbitrary regression or classification procedure on $n$ independent samples with leave-one-out cross-validation. This results in an estimate of the prediction error $e_n$ for each ...
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1answer
27 views

Prediction in VAR models

I am currently developing a Vector Autoregressive Model, and I have the model fully specified as follows: $$X_t=AX_{t-1} +Z_t$$ where $X$ and $Z$ are $n \times 1$ column vectors, and $A$ is an ...
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2answers
57 views

predictive modeling: comparing actual and predicted values in terms of accuracy

I have applied a predictive model on a hold out data set on which I know actual values of the target variable. I wonder how to compare actual and predicted forecasted values, verifying whether on ...
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10 views

would adding the probabilities in a dataset be more accurate than the individual results?

Say I have the titanic kaggle competition, but I'm not interested in the competition for predicting survival for each individual. Instead I want the most accurate estimate of total survivors on the ...
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31 views

Can you add the probabilities of a classifier to better predict an outcome?

Say I am interested in predicting the TOTAL number of people that survive the titanic disaster, NOT each individual who died. Is it possible to run a probabilistic classifier on the data getting a ...
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1answer
56 views

Mortgage loan predictive analysis

I have hundreds of thousands of mortgage loan historic records that look like these 2 examples: ...
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59 views

How to overcome prediction results that are overestimated

I'm trying to create a prediction model for estimation of continuous variable based on about 35 Independent variables.My data set has circa 27k observartions. Here is the summary of the the targeted ...
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31 views

Calculate prediction interval for SAR model (errorsarlm function in R)

I would like to predict prediction interval for a SAR model (function errorsarlm in R - package spdep). While the function predict.lm allows to set interval='prediction' parameter to predict the upper ...
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How can I predict based on several time series of many different projects?

I want to predict the time that a client takes to pay for a service that has already been received. We are talking about a construction company, so the payments are always overdue since the company ...
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25 views

What is the definition of generalization error and its justification?

I was trying to understand rigorously what the goal of machine learning is. One could frame that one of the central goals of machine learning is to obtain the best possible function ever. But what ...
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4answers
981 views

What does AUC stand for and what is it?

Searched high and low and have not been able to find out what AUC, as in related to prediction, stands for or means.
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1answer
38 views

Predicting university course marks using historic data of class mean and student's own marks

I would like to predict my course marks for this year based on the data for class mean and my own marks for the past years. What would be a good starting point for a model for such kind of data? ...
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posterior predictive of standard Normal

I want to derive the predictive posterior distribution of $y$ for the case where $$p(\tilde{y}|\theta) \sim N(\theta,1)$$ and $$p(\theta|y) \sim N(\bar{y},\frac{1}{n}) \sim N(6,\frac{1}{9})$$. By ...
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1answer
59 views

Predicting with random effects in mgcv gam

I am interested in modeling total fish catch using gam in mgcv to model simple random effects for individual vessels (that make repeated trips over time in the fishery). I have 98 subjects, so I ...
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1answer
52 views

Statistically significant difference in linear regression model predictions of the mean values

In my academic report I have a task to check whether or not mean values (for given two predictor values) predicted by the simple linear regression model are "statictically significantly different". I ...
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26 views

Explanation that the prior predictive (marginal) distribution follows from prior and sampling distributions

While I have a vague intuition that this makes sense, I am interested in the formal demonstration that the prior predictive distribution in Bayesian inference is equal to the integral over $\theta$ of ...
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1answer
60 views

Can Hidden Markov Models be used to predict next observation?

I am reading up on Hidden Markov Models (HMMs) for my research and would like to know if it is applicable to the problem I wish to tackle. My problem is to detect/estimate the next value of a ...
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1answer
25 views

MSEP and R2pred for Linear Model

I have two set of data 1-Training (Calibrating) 2-Test. With these datasets, I Fit the model using first dataset. predict using the second dataset x-variables I have to test the closeness of the ...
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19 views

How to shorten the detection time of adaboost algorithm?

I'm working on a license plate detection using OpenCV's adaboost algorithm. However, after training, it shows that the detection takes 3200ms for a single image, where the image size I used is ...
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62 views

Mean of predictive distribution

I observe independent, Poisson-distributed data $ D = \{x_1, ... x_n \} $ with mean parameter $ \mu $, i.e., $$x_i\stackrel{\text{iid}}{\sim}\mathcal{P}(\mu)$$ Over $ \mu $ I assume $ Gamma(\alpha_0, ...