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

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Confidence intervals for Tobit model in package AER in R

I use a Tobit model to predict censored data. I use the AER package in R. A toy example looks as follows: ...
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50 views

Is the `weights=` option in lmer() doing what I want?

I want to predict PGA golfer performance. I'm wondering if I am correctly giving more weight to more recent results by using the weights= option in the lmer() ...
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14 views

Binary logistic regression - SPSS

I did some regression analysis in SPSS using two binary variables: Biomarker X (0= low levels; 1= high levels), where 0 was the reference category and Obesity (0=no; 1=yes) ''Biomarker X'' was taken ...
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8 views

future prediction by inverting GAM model coefficients [on hold]

I am new to R. I am trying to fit GLM and GAM model to my species data against few variables, which I have already done using GLM and mgcv package (GAM). I got some parametric coefficients. The next ...
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15 views

Presenting and analyzing statistics on a telco fraud department? [on hold]

Im gonna be assigned to do the statistics of daily postpaid activations at a telco company I work for. They want analysis and not just presenting the stats. Do you guys have any tips on how to ...
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20 views

Which parameters to tune in CART?

I am using caret package in R to train CART model. train function seems to tune only the complexity parameter (which in a way determines depth of the tree and number of terminal nodes). Is this ...
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21 views

dangers of averaging between model approaches

I am working with some ridership data that is broken down by route, year and month. I have built and tested a whole bunch of models ranging from GLM, GEE, GENLIM, and Panel and ARIMA data models. I ...
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30 views

Fitted values from regression on first differences

I wish to predict variable $y$, and so I am tempted to estimate $$ y_t = \beta_0 + \beta_1 x_t+ u_t $$ Looking at a plot of $y$, the series does not seem stationary. Instead I regress like so: $$ ...
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26 views

Predict VAR when exogenous variable was used

I estimated my model with VAR() of the vars package in R. I included an exogenous variable. ...
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56 views

How can I force my model to predict the samples that are close to zero?

I have a large amount of inventory data and I am trying to predict when the inventory gets low using one component of the change in inventory (yes I know this doesn't describe inventory very well by ...
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1answer
54 views

Will Linear Regression choose as good of a model as any other regression algorithm given enough data?

I am in the seemingly unusual situation of having practically unlimited data. In this case, will linear regression choose as good of a model as any other algorithm in the case where the number of ...
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45 views

prediction on short time series with seasonality and data correlations

I have, say, 5 weeks of data standing for daily income of a company and I want to predict the next income. Obviously, there is a seasonality in data - every day is "seasonal" with the same day of the ...
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18 views

Statistical/ML models when observations have different amounts of input

Let's say we're predicting an employee's performance review score for the following year based on his/her performance review scores from each previous year of their employment. We might have these ...
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9 views

Discrete variables: Gaussian Naive Bayes or Bernoulli Naive Bayes?

I have a dataset of which features are: Hour Weekday Day Month 10 7 30 12 12 3 15 1 ... and with binary labels ...
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2answers
63 views

High accuracy during cross validation, low accuracy on test set

I'm currently trying to build a tennis prediction model. Unfortunately, I have some issues that I hope you could help me to handle. I have 1110 examples of matches from the year 2013, with their ...
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14 views

Calculating future states

I am working with HMM to predict the future states of a sequence. Using forward algorithm I can calculate following probability. And I need a way to calculate the prediction probability; for an ...
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1answer
46 views

Improve ARIMAX model, compared to arima model

I am trying to model an ARIMAX model on my time series. ...
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24 views

Response Surfaces and Multiple Linear Regression

Suppose I have a MLR equation $y=b_0+b_1x_1+b_2x_2 + e$. If I were to plot this equation, should it not produce a "line" ? I have looked into response surfaces and I am not sure how one would derive ...
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19 views

Theoretical properties of Gaussian Process Emulator

I am studying Guassian Prcess Emulator (GPE) to approximate computationally expensive computer models. Basically, we suppose the computer model, or simulator, is denoted by $f(x)$, where $x$ is the ...
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1answer
24 views

Getting lagged values of indep. variables to model contemporaneous values of the dep. variable

I am trying to forecast the variable, oenb_dependent: My current sample data looks like that: ...
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1answer
50 views

Multiple (not independent) response variables in machine learning

Question: How to predict the percentage of people with age < 18, 18-65 and > 65 who visit a webpage using machine learning in R? Since these percentages sum to 100 for all observations, they are ...
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14 views

Confindence of test estimation for gaussian mixture model

A simple Gaussian Mixture approach: I have a learning data $ { (x_1,y_1),(x_2,y_2),...,(x_n,y_n) } $. For learning it, I use a Mixture of Gaussian model and after learning it, I estimate new data ...
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1answer
20 views

Consumer Predicted Probability Function

I have the following data for the last year for several thousand clients: Client ID Last Interaction Date with Business Last Buy Date No of items bought Total value spend in $ I want to create a ...
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1answer
33 views

How to compare institutions based on the difference between their predicted and observed values?

I have predicted values from an OLS model. I am trying to identify if the predicted value is significantly different to the actual value for an observation. The actual value is a rate (not mean) ...
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64 views

What type of regression model do I need to use?

I am looking at the relationship between the two concepts of psychological strategy (PS) usage and athlete engagement (AE), looking to see if PS predicts AE as a whole and if certain subscales of PS ...
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29 views

What are some tests for the predictability of time-series?

I have 2500 time series which I want to test the predictability and based on that, choose the best one to forecast. Ideally I want to use a simple model like ARMA-GARCH for forecasting. Are there ...
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42 views

Time-dependent coxph output and making predictions in R

I'm trying to use a Cox proportional hazard model to predict the time until an employee terminates from an organization. There are a bunch of covariates (~20), some of them time-dependent. So I've ...
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25 views

Prediction performance of OLS and Lasso

I am running a comparison of prediction performance of two model using OLS and LASSO respectively. LASSO estimates are computed from LARS algorithm, AIC and BIC were used in model selection. In ...
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16 views

How do you read the coefficients in Structural Equation Model for prediction?

I understand that in regression, the beta weight can be used for prediction. For example: Depression =~ 1 + 0.5*Loneliness Suppose that depression and loneliness are measured with Likert Scale from 1 ...
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35 views

Prediction over the time with cohort

I'd like to modelise the evolution of the sales of a store. Here are the date I have : i.stack.imgur.com/6FsZ8.png -customers are aggregated into monthly cohort depending on the date of the first ...
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2answers
186 views

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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68 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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22 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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13 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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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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37 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
32 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
60 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
26 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
11 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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37 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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47 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
22 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
24 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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27 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
49 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
37 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
30 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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39 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 ...