The prediction tag has no wiki summary.
2
votes
1answer
56 views
Sample size with respect to prediction in classification and regression
With respect to hypothesis testing, estimating samples sizes is done through
power, and it is intuitive that increasing the same size increases
the precision of estimated effects. But what about ...
0
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0answers
24 views
Prediction of $X_{t+2}$ of an AR(2) process.
I want to find the best linear predictor, in MSE sense, of $\hat{X}_{t+2}$ in terms of $X_s'$s where $s \le t$ and $$X_t = \phi_1X_{t-1}+\phi_2X_{t-2} + Z_t\,,\, Z_t \sim WN(0,\sigma^2)$$
$X_t$ is ...
0
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0answers
36 views
Reconstructing time series data with missing values from external data source
I have a 100 year time series. But the first 30 years are missing. So I correlated the 70 years that I have with another (100 year) time series to predict back / reconstruct the missing values. For ...
2
votes
2answers
77 views
What machine learning techniques can, once trained, generate prediction despite some missing inputs?
I have a training set where the inputs & outputs are all present, but I suspect that in the data where I want to do prediction, I will occasionally encounter scenarios where a small fraction of ...
0
votes
1answer
44 views
Is there a statistical model for modelling variables that are measured in varying amounts and in different time points per individual?
I have been trying to model a dataset of variables where each individual is measured a different number of times, and on different point in time. Most of my variables are count, but some are not (the ...
1
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0answers
34 views
projecting future survival rate
I'm working on a customer retention project that predicts the probability a customer is still subscribing to our services at time T. Unfortunately, we only have the most recent two years of customer ...
0
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0answers
22 views
Should the number of parameters depend on the purpose of the model?
I am curious what are some arguments for/against increasing/decreasing the number of parameters depending on the purpose on the model.
I am currently building a model which will be used for ...
0
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0answers
18 views
Why does increasing event weight in logistic regression increase c-statistic?
I have a logistic regression model that uses all events and a sample of non-events as the training and test population. The observation weights are chosen following King & Zeng. Events are ...
2
votes
1answer
72 views
Prediction on mixed effect models: what to do with random effects?
Let's consider this hypothetical dataset:
...
1
vote
0answers
39 views
Questions regarding predict.glmpath()
I'm trying to do LASSO in R with the package glmpath. However, I'm not sure if I am using the accompanying prediction function predict.glmpath() correctly. Suppose I fit some regularized binomial ...
0
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0answers
37 views
Predict using VAR
If I arrive at an equation from VAR model; I know i can use it to predict at some relative period ahead of time by using predict(p1ct, n.ahead = 5 ci = 0.95); I ...
0
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0answers
27 views
How to specify newxreg in prediction model of ARIMA? [migrated]
I have fit the model below to my time series data. The xreg consists of a time vector that goes from 1 through 1000 and of 12 indicator variables (1 or 0) that ...
1
vote
0answers
35 views
Counterfactuals for Variables with Negative Values
Lets imagine I have estimated the following simple linear regression model:
$y_{i} = 10 + 0.5x_{i} + \varepsilon_{i} $, and want to work out the counter-factual, or what would $ y_{i}$ be in the ...
0
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0answers
14 views
Java, Weka: How to predict numeric attribute? [migrated]
I was trying to use NaiveBayesUpdateable classifier from Weka. My data contains both nominal and numeric attributes:
...
0
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0answers
28 views
Predicting Risk based on weighted data
I am looking for a formula I can use in Excel that will provide a risk score from 1 - 10 with 10 being high risk. I have a set of 15 data items (i will add more in future) which are weighted on a ...
2
votes
1answer
50 views
Relation between causal inference and prediction (classification and regression)
I was wondering what relation and differences are between causal inference and prediction (classification and regression)?
For example,
In prediction, we have predictor/input variables and ...
0
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0answers
20 views
Obtaining final classification score using AdaBoost predict function
If I understand correctly, predict.ada() returns an $n$ by 2 matrix of class probabilities for each classifier used in $n$ iterations. How can I obtain the final classification on scale of [0,1] for ...
-1
votes
0answers
30 views
Use of standardized major axis regression for prediction
Some say that standardized (reduced) major axis regression (SMA) can not be used for prediction and we should use linear regression for prediction instead. However, for X an Y with symmetric ...
0
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0answers
10 views
Writing a predict() function for the Smatr package [migrated]
How to write a predict() function for the Smatr package (specifically for the sma command)?
1
vote
2answers
118 views
How to calculate the regression variance for a GLS model?
I need to calculate the regression variance ($\sigma^2$) in order to estimate both the confidence intervals and the prediction intervals in a gls regression analysis. For the analysis, the covariance ...
3
votes
1answer
51 views
Estimating age based on height
I wonder if it's possible to estimate a child's age given the child's measured height.
I have found this height chart:
http://resource.nhi.no/resource/4281-21-hoyde-gutter-5-19-who.pdf
Is it ...
0
votes
0answers
55 views
lag in prediction outputs in one-step ahead neural network autoregressive model
I am working on an ARX forecasting problem mostly using feed-forward neural networks in MATLAB. The functional model is of the form
$y(t) = f(y(t-1),...,y(t-n),u(t))$. My data is at half hourly ...
0
votes
1answer
75 views
How can I make a predict plot varying two variables in R?
I want to plot the results of a regression model, but allowing two variable to vary simultaneously. I guess I could do that using predict() function in R, but I am running a model that does not have ...
0
votes
1answer
47 views
Linear regression with linear scale as explanatory variable
I have a dataset containing values representing monthly sales in hypothetical e-commerce website. First columns contains order of particular month (eplanatory variable) and the second column ...
0
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0answers
59 views
PCA prediction with centered vs. un-centered input data
I'm dealing spectral data. I want to classify 2 classes using principle components analysis. My PCA was constructed using prcomp(data, center=TRUE) in R. It works. ...
0
votes
2answers
159 views
What statistics should I use for evaluating the accuracy of predictions?
I have two variables representing 1) players' predicted fantasy football points and 2) players' actual fantasy football points scored. What statistics are best for assessing the accuracy of the ...
0
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0answers
41 views
Which algorithm is more appropriated for a temporal target variable that depends on others?
Perhaps the title need restatement, but I am confused on the title as I do not know the type of the problem, but only how to describe it.
Here is the description:
Suppose I have a table where each ...
0
votes
1answer
68 views
Statistical significance of ordered binary vectors
I have a program to predict some values for people. For validation, I keep track of whether the prediction is correct or not, which gives me a binary vector with a length of about 600.
To test if it ...
0
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0answers
33 views
Predict missing value(s) using existing measurement's data
I have a few measurements (6) with 13 different features (so I have more parameters than measurements).
Let's say I would have a new measurement with a few missing values, considering I have existing ...
1
vote
0answers
55 views
Estimating individual-level outcome probabilities given from group-level training data
Given multi-level data, I'm interested in estimating member-level outcomes when only group-level outcomes, along with both group- and member-level predictors, are known. I'm lacking in statistical ...
0
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0answers
29 views
audit sample prediction
I have a finite population of transaction data. The data is broken down into various sub-categories.
A subset of these transactions has been audited and determined to either pass or fail.
I want to ...
11
votes
1answer
268 views
How to predict one time-series from another time-series, if they are related
I have been trying to solve this problem for over a year without much progress. It is part of a research project I'm doing, but I will illustrate it with a story example I made up, because the actual ...
0
votes
0answers
78 views
Statistical Approach to restricting predictions between 0 and 1
I am working with tobacco prevalence data where I am smoking rates at the country level. I and am in the process of adjusting estimates across different frequencies of use(ie, daily versus occasional ...
0
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0answers
37 views
Choice of population to study
I want to do classification or clustering of my big data set on web applications.
I would like to cluster website visitors who are identified by their cookie ... which they can drop whenever they ...
1
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0answers
145 views
Comparing observed and predicted values across several measurements
As a neuropsychology graduate student with some experience in statistics (I'm usually the guy other psychologists come to with statistics problems after trying it themselves but before seeing a ...
0
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0answers
53 views
Why the prediction of neural network doesn't change?
I've created two neural networks for a prediction purposes,
the first is a network with one hidden layer and the second is two hidden layers,
I use the cross validation techniques,
the training error ...
4
votes
2answers
171 views
Time series prediction with non-constant sampling interval
I have some data which can be modelled as such: each data sample $S$ is a series of discrete signal values $S(t_n) \in \{-1, 1\}$ measured at times $(t_{n, S})_{1 \leq n \leq N_S}$. The number of ...
1
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0answers
62 views
Markov Chain Prediction with unknown states
I want to make a prediction of the next state based on a training and test dataset. So I split my data into a train and test set and calculate the MLE on the train set and want to predict the next ...
0
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0answers
53 views
Significance index of unlabeled data prediction
I have a training set used to train an SVM classifier, the model found is used to predict a dataset of several unlabeled examples.
I would like to know how to extract an index of the goodness of the ...
2
votes
1answer
229 views
Getting the good prediction standard error with R and/or SAS
Consider for instance the balanced one-way random effects ANOVA model:
$$(y_{ij} \mid \mu_i) \sim_{\text{iid}} {\cal N}(\mu_i, \sigma^2_w), \quad j=1,\ldots,J,
\qquad
\mu_i \sim {\cal N}(\mu, ...
0
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0answers
27 views
Problems with spBayes package and prediction
I have successfully fit a number of spatial models with spBayes and am now trying to test their out of sample predictions. However spPredict always seems to fail with Cholesky decomposition errors. ...
2
votes
0answers
83 views
time series with different length: feature extraction and classification
I have a binary classification problem, where each data point is multi-channel time-series, which can be represented as a matrix TxF, where T is the time-series length, and F as the channels number.
T ...
1
vote
1answer
197 views
Best predictive Cox regression model using c-index and cross-validation
I want to explain the problem I have in this moment to know what do you think about the implementation I am designing.
I have a set of 40 genes expression data as binary variables (overexpressed yes ...
0
votes
0answers
73 views
inverse predict from binomial glm - how to obtain confidence intervals?
I am trying to use a glm with a binomial distribution (logit link) to analyse data from a dose response curve for the lethal effects of different bacterial strains. I now want to obtain estimates of ...
0
votes
1answer
174 views
How do I use vector auto regression using the statsmodels library in python?
Sorry about the rookie question but I have been at the documentation for three days and couldn't figure much out. (Link To documentation page)
First, how do I load my own data? Must I store it in a ...
1
vote
2answers
106 views
I need a model that can predict based on multiple variables. How do I get started?
I have a problem where I have to predict a variable X that is dependent on several other variables a,b,c,d... I have the data containing the values of these variables a,b,c,d.. and also X up to a ...
1
vote
2answers
54 views
Predictions when multiple outcomes
Background and Setting
I have data of this format: on each subject the list of exposure to some subtances, some demographics and then a multiple response (whether the subject developed a disease or ...
3
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0answers
76 views
Long-term predictions [closed]
My question might sound a bit vague and probably too broad. It is because I do not expect straight answer. I'm starting a part of my PhD were I need to analyse a long-term prediction of reliability. ...
1
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0answers
67 views
How do you predict the value of new instance, when the training data were normalized?
I estimated a Partial Least Squares model where the X matrix had normalized columns. Now I want to predict the value for a new instance (which is a frequency vector summing to one.) I assume that if I ...
1
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0answers
46 views
How would one calculate the percent error on a vote?
Maybe I'm not asking for the right measure. Basically, there are 9million votes already in, and 4.8million no, and 4.2million yes. There are a million votes left to count. What are the chances that ...
