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

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Statistical Model: How much will my open bar at my wedding cost?

I am getting married in November in Mexico and after fidgeting with my wedding budget, I was wondering if anyone had any insight into how I should approach my problem. Thought it was relatively ...
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20 views

Granger Causality and Regression

I have an enquiry regarding the Granger Causality analysis. It is said that it is performed to check whether “X causes Y”, or to put it differently, whether X contains any predictive information with ...
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20 views

In logistic regression, what is the expected correlation between prediction and the dependent variable?

In multiple logistic regression: what is the expected covariance between the dependant variable $Y_i$ and prediction $expit(X_i\hat{\beta})$? what is the expected covariance between the dependant ...
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12 views

Interpolation of Data Value using Optimized Weighting of Its Features

I have a question regarding "Interpolation" / "Prediction" of a value. Assuming we have a data set $ { \left\{ \left( {x}_{i}, {y}_{i} \right) \right\}}_{i = 1}^{N} $ where $ {x}_{i} \in ...
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11 views

Predict missing tail data in one vector based on complete data of another vector

I have two sets of paired data. The first set is a complete population grouped into 51 ascending groups as follows: ...
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1answer
31 views

Data analysis and prediction algorithm recommendation

I need some help. I'm a programmer but I'm not familiar with data science or analysis. I've been given a project which I have to do a research with a list of CSV data files. I converted some of those ...
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1answer
28 views

Beyond least squares: how to choose a predictive model or algorithm? (reference request)

There are dozens of algorithms one can use to build a predictive model. What books or studies exist that can help one determine which algorithm to use? Elements of Statistical Learning spends a lot ...
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2answers
50 views

How to predict property value using lat/lon?

I have lat/lon and property values for households in a particular region. Format: Lat Lon value 32.2 -98.22 120000 .... Now I have new data of the ...
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1answer
19 views

Prediction with time series model

I have a data from last 28 years about the yield of cornstover on different states. I want to make a prediction for next year using this data. I am entirely new on time series model and don't know ...
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18 views

Linear regression estimation using multiple data points

I have a linear regression model, and I'm using it to predict outcomes based on two points of data that I am fitting to my equation. I'm collecting the data points manually with a stopwatch, so ...
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1answer
10 views

Clarification on Prediction with a Regression Model using Centered Variables

As I understand it, for a regression model, centering the variables around their means can be helpful since it makes the intercept term the expected value of $Y_i$ when the predictor variables are set ...
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33 views

How to go from sparse matrix to linear regression model (using SVD)?

I am trying to replicate the Kosinski, Stillwell, & Graepel (2013) study about predicting private traits and attributes from Facebook like data for study purposes. First I have admit, however, ...
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1answer
38 views

How do you get Count R2 in R (with missing data)?

I am doing binary logistic regression in R and I need to calculate the Count R squared for various model specifications. Count R2 is the number of correctly predicted observations using the model ...
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1answer
20 views

Model selection in the classification problem with costly information

Let's assume we have a $X_T$ matrix of $N$ variables and $Y_T$ available for training a model to solve classification problem for variable $y$. Normally, we can use all $N$ variables for training and ...
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1answer
13 views

How can I test if a predicted value is statistically different to the corresponding observed value, accounting for sample size of the observed value?

I'm trying to test whether a observed value is statistically different to it's corresponding predicted value. The observed value is a rate of a particular healthcare treatment, the predicted is the ...
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20 views

How to maximize prediction for positive values (or negative values) instead of Accuracy using train function in R

I want to select and assess (using cross validation) several models in order to predict a dichotomous variable using train function in ...
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1answer
39 views

plot ROC curve from glm model using gaussian model

I have some data (322 x 4) that looks like that ...
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1answer
30 views

Does a theoretical “perfect (accuracy) score” exists we could target for a given dataset?

My question is the following : You have a dataset, and you want to determine theoretically what accuracy score (or other way to measure performance such as AUC, etc.) a "perfect" model could get on ...
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1answer
20 views

Combining confidence intervals from several regression point estimates

I have 13 point predictions from 13 independent linear regressions, each prediction with a 95% confidence interval. I want to sum the 13 predictions and calculate the 95%CI for the summed value. ...
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1answer
28 views

gam models with random effect R

I am modeling fishery CPUE as a function of a number of a number of covariates using a GAM approach that includes fixed and random effects. I understand that there are limitations with regards to ...
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1answer
72 views

Difficulties obtaining valid predictions when using interactions

I examine long term trends (2003 to 2014) for a continuous dependent variable. I want to predict the mean each year in relation to income category. Income is arranged in quintiles, from 1 (poorest) to ...
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45 views

Is there a name for this fallacy?

I sometimes encounter a view that only perfect forecasting is really forecasting. For example, if I claim that I have a model which forecasts election results, people will think I'm making the ...
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34 views

Variance of the logit of the mean of the predicted values of a logistic model

I have a logistic model, and I am trying to calculate the standard error of the logit of the mean of the predicted values. Here an example with R: ...
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2answers
46 views

I am running a logistic regression model and get very low predicted probabilities

I am running a logistic model for catastrophic health expenditure (CHE) in Argentina. The sample size is 22500. I followed Xu et al. methodology to define CHE and adjusted for 8 socioeconomic ...
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53 views

Rounding up/down predicitions for a binary outcome

I'm quite new to the subject of deeplearning and statistics, so please bear with me. I was assigned to build a model that will try to predict the winner in a chess game. Given a state of a chessboard, ...
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13 views

Forecasting values along with corresponding years [migrated]

I have a sample data set (named as s3) in the following manner: ...
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12 views

Generating predicted mean values and CIs across different groups in lme4

I’ve run a mixed-effects model with crossed random effects in glmer and ultimately want to show a bar graph depicting mean predicted values (and associated confidence intervals) across years within ...
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1answer
29 views

Multivariate multiple linear regression model

I have 2 response variables (Y1, Y2) and some independent variables. I need to predict both Y1 and Y2 using the same set of predictors.In other words I need to fit the model: $Y=XB+E$ where: $Y$ has ...
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21 views

Truncated normal hurdle (for corner solution responses): how to use results for prediction?

I have fitted a (Cragg's) truncated normal hurdle model over a dataset in which the dependent variable is either zero or positive. The model consists of two parts: a probit which estimates the ...
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8 views

Regression model with percentages

I have a dataset with 5 dependent variables ($y_1$,$y_2$,$y_3$,$y_4$,$y_5$) and some independent variables. Each dependent variable is a percentage (so it goes from 0 to 100). The sum of the 5 ...
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1answer
21 views

Common approaches to illustrating “central” responsiveness in linear regression predictions when including categorical variables?

Consider the simple linear regression framework: $y=\beta_0+\beta_T T+X\beta_X+\varepsilon$ Where $T$ is an indicator for treatment in an RCT and $X$ is a vector of controls. One common approach I ...
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1answer
34 views

Prediction for a large number of discrete numbers other than classification and regression

I am dealing with a problem where the output of my model, can have numbers like 1-3000 (around) (score in a game). This is like a score in a game. Giving a least squared error setting, for a model, ...
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37 views

How good is my computer aided diagnosis system vs the expert?

I have developed a systematic method that attempts to quantify the amount of disease present in medical images. E.g. % area abnormal. In my dataset, I have healthy people with no disease, and people ...
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15 views

Multivariate prediction using Bayesian Nets

I have a set of continuous variables X, a set of ordinal variables Y and a deterministic function from Y to a continuous value u, u= f(Y). I want to build a Bayesian Net for X and Y, where there will ...
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9 views

Using a neural network for prediction

I am new to neural network and want to see is it a valid approach for predicting data points that are repeatable in time? For example, the sequence looks like ...
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1answer
34 views

optimal sequential sampling in gaussian process models

Let's say we have a one dimensional dataset of 24 points along with their responses. I am reserving three boundary points for testing (i=1,23,24) and i am fitting a Gaussian process model based on a ...
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21 views

Too small baseline predictors

I'm trying to implement a recommender system, based on SVD-algorithm. I have a matrix with binary rates, i.e. 0 and 1. This matrix is very sparse. I'm using a formula for learning process: ...
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2answers
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1answer
31 views

How do risk models deal with state changes over time?

Let's say you are trying to predict if a machine is going to explode (0) or successfully complete its job (1), and you are trying to determine the impact of certain states on the machine. So say the ...
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1answer
19 views

Probability two predictions (from linear model) are different from each other

Suppose I fit a linear model to a bunch of training data and make two out of sample predictions: $P_1 = .5$ with standard error $SE_1 = .08$ and $P_2 = .7$ with standard error $SE_2=.09$. What is ...
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19 views

Prediction of the probabilities in the stochastic process

The system can have n different states. At every time period it might either stay in the previous state or move to another state due to two possible reasons (A and B). I need to predict three ...
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1answer
79 views

Gaussian process regression: leave-one-out prediction

According to Dubrule's Cross validation of kriging in a unique neighborhood, it is possible to compute leave-one-out the gaussian process prediction $\hat{Y}_{-i}(x_i)$ at a point $x_i$ from the ...
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31 views

lme4 variance of predictions

I want to calculate standard errors of predicted outcomes from a mixed-effects model estimated via lme4's glmer function. Since my question is quite basic, I use a sloppy notation and hope that it ...
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0answers
18 views

Classifying with a distance/error metric

I have a bunch of data of the form (x0, x1, x2) -> y (everything is categorical data), and I want a decision/classification rule for predicting y a metric on y's space (there is no "natural" metric) ...
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21 views

Using nls To Model

I'm trying to use nls model certain curves that I found in a dataset. I'm not sure how I can give example data, but here are the curves as they look right now: I tried using ...
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15 views

How does micro precision work

I am trying to figure out how micro precision works and have followed some tutorials online. But some things don't make sense at all I copied the part of the text from a website online ...
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1answer
76 views

Poisson regression for count data - predictions

This is probably an elementary error in either my understanding or my R implementation: I am trying use a Poisson model to make some predictions. The original data is discrete count data. I would ...
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1answer
18 views

Best classifier for data with text among features

What is the best classifier when we have data a train set within a text among features. Here is the situation: I have a train set X (6 features) and a label 2 of the features is a text. Than I need ...
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2answers
78 views

Calculate prediction values for linear curve estimation for next 5 intervals

Below is my code with sample data as in screen shot ; in that i got response for only 21 to 33. My requirement is to get response for 34, 35 , 36, 37 Sample Data Below is R code ...
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1answer
34 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 ...