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Questions tagged [prediction]

Prediction of unknown random quantities, using a statistical model.

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5 views

Comparison of MAE and Mean to illustrate the error magnitude

I have predicted a time series with positive, zero and negative values. As error measurement I used the Mean Absolute Error (MAE). In order to give the reader of my paper a better understanding ...
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Kalman filter multi-step prediction

I have historical data for five correlated time series, denoted by $\{\mathbf{x}_t\}_{t=-m}^0$, where $$\mathbf{x}_t\equiv[x_{1t}, x_{2t}, x_{3t}, x_{4t}, x_{5t}]^\intercal.$$ I already have ...
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1answer
10 views

Use of expression “statistically significantly predicts” based on in-sample analysis

Suppose one estimates a linear time series model $$ y_t=\beta_0+\beta_1 x_{t-1}+\varepsilon_t $$ and finds that $\hat\beta_1>0$ and the $p$-value associated with $\hat\beta_1$ is lower than the ...
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Find the CI for the probability of having diabetes for patient in the 10th row in the test data using bootstrap procedure [on hold]

I have a logistic regression model which I got from the stepwise procedure selected by BIC. I used the training model and glm() to fit the logistic regression model....
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1answer
31 views

Legitimacy of Regressing Actual Values on Predicted Values for Better Residual Sum of Squares?

A coworker of mine recently performed an analysis where after training a simple linear model, he regressed the actual Y values against his model's predicted Y values, and applied this regression's ...
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17 views

What statistical test is most appropriate when my data consist of multiple series, each based on an individual sample?

I'm trying to determine the effect of an interferent $X$ on the measurement of a substance $Y$. Ultimately, I'm looking to predict $Y_{actual}$ within a confidence interval, given $Y_{observed}$ and a ...
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11 views

randomForest prediction for zero-size nodes

I have just realized that despite the documentation ...
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21 views

survreg predict default options

Given a suvreg model, for example, lfit <- survreg(Surv(time, status) ~ ph.ecog, data=lung) I get the same result if I ...
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20 views

When is it appropriate to model data as a Stochastic Process? [closed]

I understand the question may be poorly worded, but please bear with me. I have a background in computer science and mathematics, but never took any upper-level statistics courses. I currently work ...
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11 views

Unbiasedness and Variance of Predictions

Here is the problem I'm working on: I'm not quite sure if I'm showing either unbiasedness property right, and am stuck on finding the expressions for the variances. Here's what I've done so far. (a) ...
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35 views

Adjustment of the forecast of a time series for the analysis of a system

I have a simulation model of a system which receives a forecast of a time series as input. In my scientific work I would like to examine how the performance of the simulation model behaves in relation ...
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21 views

predicting X values from smooth.spline

I have an existing smooth.spline object, and I wish to estimate X values for a set of new Y values. I see that ...
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22 views

Incorporating head to head results in model predicting winner of multi-player game

I am using a rank-ordered logit model to predict the winner of a multi-player game (think Fortnite). Among other individual-level factors (e.g., strength of each player, experience or number of games ...
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16 views

In what step should I try to find a best thread cut-off point for binary classification? [duplicate]

I am working on an imbalanced binary classification and wondering in what step I should find the best optimal threshold cut-off point. When I tried classifying the dataset with the normal probability ...
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2answers
84 views

Differences between a frequentist and a Bayesian density prediction

What are some essential differences between a frequentist density forecast/prediction and a Bayesian posterior for an outcome of a random variable? Of course, there will be differences in how they ...
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2answers
45 views

How to train and assess prediction models when data are imperfect (miss some true cases)?

Consider the following example. Suppose your labeled dataset includes images of dogs and you want a computer program for recognizing dogs in images. The problem is that your data are imperfect because ...
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19 views

How to take advantage of historic data while doing churn prediction?

The problem: Predict customers who will downgrade their bank account category 2 months in advance. The data: 100's monthly variables for each customer for the last year. At first, I thought I could ...
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1answer
15 views

Optimizing parameters for a classification model which predicts unseen future data

In my understanding, typical gridsearch (e.g. sklearn's GridSearchCV) evaluate a predefined parameter space and determines the optimal set of parameters within this space through iterating through the ...
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24 views

How to address impossible values in a regression prediction interval?

Background I've performed a regression analysis on a toy data set to predict GPA from height. I want to compute the predicted GPA value for a given height value and also compute a confidence interval ...
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27 views

posterior predictive distribution for latent dirichlet allocation model

I want to obtain posterior predictive distribution on the LDA model, actually, I want to predict n next sample ( words in this model). can anyone help me? I attach the LDA model here, and it is ...
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1answer
25 views

how to validate large amount of unlabeled data by using small amount of labeled data?

I have to predict large amount of unlabeled data with the help of small amount of labeled data by using classification model. How can I validate that this prediction is true or not ?
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12 views

Unplausible results in Hansens SPA-Test due to max(0, x)

In applying Hansens Superior Predictive Ability Test, I am receiving inplausible results for very bad alternatives, i.e. the p-value is 0 but should be in higher regions where you usually do not ...
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29 views

Sales prediction for the next year

I Have a homework problem. I need to predict sales for the next year and I have a condition that TRP for the next year = 4000. I don't know what I should begin with first. ...
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17 views

Draw chance in games as a range?

I am working on my first project with a lot of data and outcome prediction. One goal is to calculate the expected outcome of a game between two parties. (Parties don't have to be of equal "strength" ...
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18 views

What is the Degrees of Freedom of linear combination of parameters from a OLS regression estimated on imputed data

I've estimated an OLS regression on imputed data with results combined using Rubin's Rules. I'd like to get the confidence interval for a linear combination of coefficients. However, because I'm ...
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19 views

What are the techniques to predict revenue of a new shop using nearest shops?

I am trying assign a revenue for a new shop based on location. I have the data of nearest few shops. What are the techniques available to propagate/predict revenue a of new shop ?
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1answer
23 views

Using predictors observed at different times in regression

I want to predict vegetable yields for each field using samples of the vegetables. Some fields have multiple samples taken over the season and some only have one sample. Sample data consists of ...
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50 views

R predictive plot with cplot and GLM

I am using the cplot() command from the margins package to analyze predictive outcomes across different model specifications while coming across two issues. Below ...
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1answer
70 views

Predict time series with a very small dataset

I have a problem with a dataset where I do not exactly know how to work with. Here it is: ...
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80 views

Is it correct to use the model provided by LASSO to predict an outcome?

I know my question will sound a bit stupid to the experts of the field but I can't find a good answer to this point. I have 214 covariates and a binary outcome. The total number of positive and ...
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1answer
24 views

Interpreting predictive models in the presence of omitted variables

Suppose the best predictive model from a set of possible models is a univariable model, due to lots of moderate correlations with other variables for example. However, if I use this model for ...
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36 views

Why does LASSO predict random data “well” during leave-one-out cross validation?

pre-amble: While investigating different cross validation strategies for small sample size dataset's with relatively large number of features I came across this peculiar result. While making a simple ...
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1answer
22 views

How to predict if an occurrence will repeat (e.g. repeat customers)?

I have a data set showing whether or not people bought ice cream from a specific stand and whether or not they ended up being return customers. ...
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14 views

Match forecasting for games with multiple win conditions

I'm trying to make a model for forecasting the results of games with multiple win conditions. For example, we may have a game where the first player to score a certain number of points wins, or the ...
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1answer
990 views

If I have a 16.67% fail rate (N=24) & I do another 24 tests, what is the likelihood that I get 0 fails by chance?

Doing some code testing and I have a pre-fix environment where I ran 24 test scenarios and 20 out of 24 worked as expected—only 4 (16.67%) failed. In the code where the fix exists, if I do another 24 ...
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31 views

Limit the upper predicted values in r

I'm trying to predict rainfall. But the log model gives very high prediction for certain values. Please check the plot for actual vs predicted values. Is it possible to limit/restrict the upper ...
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1answer
43 views

Is time series analysis suitable for long term predicting/forecasting?

Can I use time series analysis to predict/forecast long term ? Example using ARIMA, how can I explain the back of the theory its?
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59 views

Predicted individual treatment effect with continous treatments

I'm trying to apply Rubin's counterfactual model in an observational setting using machine learning predictions to simulate the unseen treatment-outcome pairs, according to https://www.ncbi.nlm.nih....
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60 views

Time series predictions look suspiciously good [closed]

I am working on a time series forecasting problem. For this, I am training a recurrent neural network in Keras (mostly following the guidelines from this blog post by Jason Brownlee). My problem ...
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3answers
355 views

What is acceptable in a prediction model accuracy? [duplicate]

We have developed a Predictive Model to show certain elements increasing and decreasing in certain locations of country. What is acceptable in a prediction model accuracy?
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1answer
24 views

What is the difference between machine learning approaches and Fourier series to fit a curve to data graph?

As I know machine learning(at least in some problems) tries to fit a curve to data graph. And I think Fourier transform tried to do it. But machine learning use a hypothesis curve with the formula ...
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29 views

How can I reduce the noise of prediction graph? [duplicate]

I am trying to use LSTM to predict a time series data as you can see in the following image, the predicted graphs is very noisy: The original data is looking like this: That I normalized it like ...
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21 views

How can I compare the effectiveness of a regression model for different datasets

I have a multiple linear model that works on different datasets. suppose that the first dataset produces y in range of [1,100] and the second one in range of [1, ...
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16 views

What do you think is the best method for prediction for network structures

Open Ended Question Here. Suppose that you have 10000 samples for 100 binary explanatory variables. Approximately every explanatory variable has a fixed probability of being 1 (say 25%). The outcome ...
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15 views

(VAR/VECM) Difference between fitted value and predicted value using in-sample data

My understanding of the mechanism of generating fitted values of VAR or VECM is much like lm() (perhaps since VAR/VECM use linear regression to estimate coefficients?), where the data is just used to ...
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27 views

How to use Hidden Markov Model for predicting the last state in set of sequences? [duplicate]

I have a dataset consisting of a set of sequences as follows: ...
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1answer
40 views

Logistic regression: use of the term “prediction”

I would be grateful for any advice on this. I am currently working on an analysis where we are trying to identify what variables would be most useful in predicting a particular binary outcome. We used ...
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1answer
32 views

Modeling probability mass over time for prediction

Consider a discrete random variable $X$ with three possible realizations $x_1,x_2,x_3$. This variable is observed over time, with the number of observations per point in time varying. The top ...
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13 views

Big difference in random forest test subset error and other subsets

I'm using R "randomForest" package for predicting stock prices. I have more than 3000 observations and 90 columns. I have excluded my last 150 days from data set and divide the rest of my data to ...
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26 views

Prediction model with lagged target variable as input

Including a lagged version of the target variable as input naturally improves the accuracy. A disadvantage I observe is that almost all the weight (e.g. in linear regression) is put on that feature, ...