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

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2
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1answer
77 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 ...
1
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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 ...
0
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0answers
17 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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0answers
30 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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0answers
16 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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0answers
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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0answers
15 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, ...
0
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1answer
38 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 ...
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0answers
19 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 ...
0
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0answers
22 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 ...
1
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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
40 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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0answers
20 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 ...
1
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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 ...
23
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6answers
286 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 ...
1
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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
votes
1answer
45 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) ...
0
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1answer
48 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 ...
1
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0answers
27 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 ...
4
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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. ...
0
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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
votes
3answers
172 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
23 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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0answers
52 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
38 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: ...
0
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0answers
27 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 ...
-4
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1answer
47 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,
0
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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 ...
1
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1answer
25 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, ...
0
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0answers
38 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 ...
0
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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 ...
0
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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 ...
1
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2answers
98 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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0answers
63 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
76 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 ...
1
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1answer
80 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 ...
0
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0answers
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
62 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
68 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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0answers
42 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} ...
1
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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 ...
0
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0answers
18 views

Radial basis network character recognition

I want to develop a simple character recognition program by implementing a given neural network kind; a simple command line-type is enough. The radial basis function neural network was assigned to me ...
0
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0answers
102 views

Which prediction algorithm fitted for prediction in R

I was used R and mongodb for finding predictions of next date outcome for that I write R code as below ...
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0answers
24 views

Logistic regression and ratio cases to non-cases in sample [duplicate]

I have a dataset with approx. 13,000 cases in total, and approx. 1,000 cases have the outcome I am interested in predicting (sentenced to imprisonment). I have run a logstic regression on the whole ...
3
votes
0answers
42 views

Is there justification for using cross validation scores as model averaging weights?

Bayesian model averaging uses approximate Bayes factors. Some researchers use AIC to weight models. Is there justification for using, say, the Brier score, median absolute deviation, or other such ...
2
votes
1answer
46 views

How to compare two different predictors

I have developed a new predictor based on neural networks for a specific problem in bioinformatics. This predictor takes as inputs several features and returns a boolean target value. Additionally i ...
0
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0answers
35 views

Which algorithm given this plot? [duplicate]

I computed a feature x that I use to predict y which is a probability of being a certain class. Raw data in R format for (x,y) ...