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

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prediction from incomplete observations

Suppose I have a linear model predicting class-membership from a set of predictors. Now, I am going to classify a new observation which has, however, some predictor values missing. How can I deal with ...
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15 views

Choice of loss function in correlation matrix prediction

There is a random vector $X=(X_1,\ldots,X_p)$, with $p$ large, $E[X]=0$ and $V[X_j]=1\ \forall \, j=1,\ldots,p$, but the correlations are different from zero. We cannot assume multivariate normality ...
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26 views

what is the return value of predict in the fGarch package

I have a question about a quit sophisticated model for a time series. Suppose $ \{X_t:0\le t\le T\}$ is a time series. The plot of autocorrelation function and partialcorrelation function suggest and ...
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1answer
29 views

Computational Complexity of Prediction using SVM and NN?

I've seen answers discussing the complexity of training SVMs and neural nets, but how about for predicting new responses once a model has been trained? For context, I'm working on an app that should ...
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0answers
14 views

How can we predict random non-balanced events?

Prediction is the ability to statistically foretell the occurrence of future events by learning from historical data. In all the cases, if we have a large enough sample of data on how people behaved ...
3
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28 views

Correlation & Regression Prediction [on hold]

I have a homework question. I have solved most of it already, but am unsure how to proceed with one specific part that involves prediction (Parts B & C). I am not looking for anyone to just give ...
2
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1answer
81 views

Adding predicted probabilites from logistic regression instead of using cut value

I am using a logistic regression model to predict a binary decision (purchase, don't purchase) based on several independent variables (income, age, education, etc.) for a population of individuals ...
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0answers
18 views

How to calculate standard errors of a non-linear model prediction?

I'm trying to understand how to show the prediction error of a model fit in R using the non-linear least squares function nls. Although there is an argument ...
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0answers
21 views

How to further reduce predictive error in a regression tree model

I had fitted 480 records to a regression tree model, and validated it with a validation data set of 120 records ( I used a 80/20 split ), I calculated the predictive error of MSE to be about 5.6037. ...
2
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31 views

Neural Network Error Plot Odd Effect

I'm using R to fit a neural network to data generated by the formula $y = x^2 + \epsilon / 2$ where $x \sim \mathcal{U}(0, 2)$ and $\epsilon \sim N(0, 1)$ (very simple, right?). The following plot ...
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17 views

Assessing the accuracy of prediction (count data with few values)

I am using three different models (NB2, Poisson, hurdle) to construct a prediction function for the count data with values varying from 0 to 7 (77,93%; 15,91%; 4,15%; 1,33%; 0,51%; 0,12%; 0,04%; ...
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15 views

Papers on resource prediction over time series with asymmetric information?

I'm looking for resources to help me solve an issue of resource prediction. We can make a number of observations of the resource over time, but the way in which the resource changes is affected by ...
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17 views

Collaborative Filtering, matrix decomposition, and incorporate various kinds of data

Just about every matrix factorization (e.g., SVD++) has some matrix that includes a n users and m (e.g.,) ratings. Here is my question, how do you include information like demographic information, ...
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1answer
39 views

Effectively using coefficients from poisson regression

This is maybe annoyingly easy for some, but I am completely new to regression. As an example, I shall use the data set in R, called mtcars. I am interested in the ...
0
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0answers
21 views

Expected prediction error - derivation

I am struggling to understand the derivation of the expected prediction error per below (ESL), especially on the derivation of 2.11 and 2.12 (conditioning, the step towards pointwise minimum). Any ...
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0answers
24 views

How do the ROC cutoffs relate to predictors?

Apologies for this rather simple question, but I haven't been able to find a definition online. What does the ROC cutoffs represent for the AUC package? Specifically, how does it relate to the ...
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0answers
35 views

Correct model to use for count data

I've been working on an assignment for a while as a part of my final qualification thesis. I'll try to describe my problem in a nutshell. There is a small cable TV channell which sells some types of ...
2
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0answers
42 views

Time series prediction where each datapoint has a sequence

I am Computer Science major, and new to stats, so please bear with me and point me to the right direction if what I'm asking is pretty obvious. I have a dataset, where each data point consists of ...
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27 views

Prediction algorithm in ctree() function in R party package

I have a model that predicts categorical response using the conditional trees, ctree() function in R package "party". I am able to get predicted responses on the new data set after training the model ...
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1answer
20 views

Characterizing relationship between two datasets

I have two data sets of electricity prices in a given region, one with data at 5 minute intervals and one with just the hourly values (which are almost, but not quite, averages of the 5 minute values ...
24
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6answers
296 views

Standard errors for lasso prediction using R

I'm trying to use a LASSO model for prediction, and I need to estimate standard errors. Surely someone has already written a package to do this. But as far as I can see, none of the packages on CRAN ...
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0answers
8 views

Predicting the growth of a social network

I am building a predictive model for the growth of the amount of users of a new p2p protocol inspired by bitcoin and I would like to use historical data collected from the growth of major social ...
2
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1answer
47 views

Generalised linear model fitted values

I have ran this model in R: glm(alert ~ water.height + ssp*ssp.zone + log(count) + ssp*days, family=quasibinomial, data=ScanSampling_sub_alert) ...
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1answer
56 views

How to predict binary outcome from a glmm model

Suppose I fit a generalized mixed logistic model such like that: ...
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0answers
19 views

What model to use to predict behavior of a group based on past behavior of group members

What model to use to predict behavior of a group based on past behavior of group members. I am using an analogy of sports team. Say we have data for individual players of sports. The data is the ...
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0answers
28 views

What is the meaning of the term “enrichment” when performing cross-validation?

Trying to understand a discussion of a 5-fold cross-validation process to validate a predictive model and its results, there is a particular phrase which has me stumped, i.e.: The predictions of ...
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2answers
64 views

Prediction interval for my bus journey

I take the bus to work and I am trying to make a prediction interval for the journey time to work so that I can leave the house and be 99% sure I will get to work on time. The journey has 2 parts. ...
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0answers
6 views

Predicting Required Number of Vehicles

I'm trying to predict the number of vehicles per model required to maximise utilisation and booking volume but I've hit a brick wall. I've done some exploratory analysis and utilisation is affected ...
2
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3answers
174 views

Can statistics really be used in education to determine test scores?

I am a middle school teacher. My district prides itself on having the kids take 3 tests during the year to predict their score, and my teaching, on "the real test" at the end of the year. My question: ...
2
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0answers
25 views

Multi-output decision tree

I have a dataset of 1000 tumours described by 6 parameters (my independent variables). For each tumour I have a value of the accuracy of 8 different segmentation methods. I would like to build a ...
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61 views

Predicting and calculating test mse using cforest R

I'm new to the cforest package and am trying to create a cforest model to predict a new test set and calculate the model test MSE. My data is split into d.train ...
2
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0answers
55 views

Predicting Next Likely Outcome of Binary Time Series?

I'm trying to approach the following problem: Danny & Johnny are professional basketball players. Each day they meet, and play for a while. Whoever scores the most points is declared winner for ...
3
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1answer
39 views

How to scale new observations for making predictions when the model was fitted with scaled data?

I understand the concept of scaling the data matrix to use in a linear regression model. For example, in R you could use: ...
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0answers
28 views

Single ARMA model for multiple time series

I have 365 days of hourly data (24points each) of a prediction error (realised -pred_day_before). I want to model the evolution of the prediction error as an ARMA process. Matlab System ...
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1answer
49 views

How does Support vector machine predict the classes for the test points? [duplicate]

Could any body explain that " how does linear svm work for prediction in the classification process?" Many thanks,
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1answer
14 views

Prediction using multiple training sets

I have multiple different training sets($TS_1$,$TS_2$,..,$TS_n$) and one test set $TS$. I have calculated the prediction measures precision, recall, and F-measure for each pair ($TS_n$,$TS$). Is ...
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1answer
28 views

How to compare observed and expected outcomes for continuous data

I am working on some data, more specifically some predictions of some outcomes. The predictions vary on the continuous scale, between $-3$ and $3$. They can for example be: $x_1=-2.4, x_2=-2.1, ...
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0answers
41 views

How can I use R to build an ordered logistic regression model and to measures its performance?

I want to use R to build an ordered logistic regression model and to measures its performance. My goal is to predict whether an athlete will get gold, silver or bronze. I started with logistic ...
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0answers
27 views

Building prediction model with estimated predictor variables

I'm planning to use logistic regression with multiple (~5) predictor variables to predict whether something happens or not. I have two types of predictor variables: known (measurable) variables and ...
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0answers
20 views

MCA to Predict New cases?

Just wondering if we can use MCA (Multiple Correspondence Analysis) to predict new cases's classification? Map new cases on to the Biplot to see which direction on the axes it is closer to? How do ...
2
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0answers
16 views

How to construct a design matrix for coxph with pspline term?

I am wondering how to reconstruct the design matrix for a coxph() model with a pspline() term. For example, if I fit the ...
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2answers
101 views

Comparing predictions from models

I'm wondering how to compare the predictions of three different models - a logit, a probit and a linear probability model - when predicting a binary outcome. I'm currently working with simulated data, ...
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64 views

plot: straight regression line and prediction bands

I have realized a multiple linear regression. To know how well my model does in terms of prediction, I can compute prediction intervals bands and decide if they are narrow enough to be of use. If ...
0
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1answer
77 views

Predicting class probabilities in regression based on area under the curve

Logistic regression models the log odds. That is for rv $Y$ which is binary logit$(Y=1)=X\beta$. Then with this model, you can estimate the class probabilities and hence prediction or ...
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1answer
81 views

Predicting new data using a Case-cohort Proportional Hazards Model

I am fitting a Case-Cohort Proportional Harzards (CCH) model using the Survival (version 2.37-4) package in R 2.15.3. Normally with a Cox Proportional Harzards (coxPH) model, I can use the survfit ...
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46 views

Time Period Predictive Modeling

I have been implementing some classification algorithms (Naive Bayes, SVM etc) recently on the iris data sets to get head start into the data science field. I enjoy working on machine learning ...
3
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1answer
65 views

SE of fit versus SE of prediction

I would like to get the standard error on a prediction. Using R glm, I can get the SE of the fit for a specific prediction: ...
3
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1answer
69 views

Regression model for prediction using intermediate outcomes

Is it appropriate to include intermediate outcomes in a predictive model? It is quite clear that one should not control for post-treatment variables / intermediate outcomes when the goal is causal ...
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44 views

Bayesian hurdle model and predictions

I fitted a Bayesian hurdle model assuming a Poisson distribution: $ P(Y_i=y_i) = \begin{cases} 1-\pi_{i} & \mbox{if }y_i=0\\[0.5em] \pi_{i} \frac{\lambda_{i}^{y_i} ...
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1answer
49 views

Predictive accuracy and correlation of inputs

I am reading Judgement under Uncerntainty and in p.65 it is stated that in the normal linear model, correlation of input variables decreases the predictive accuracy (in contrast to the human ...