The prediction tag has no wiki summary.
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1answer
189 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
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2answers
107 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
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2answers
56 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
78 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
69 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 ...
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0answers
48 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 ...
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0answers
30 views
How to get the prediction values for two response variables from random forest? [duplicate]
Possible Duplicate:
Prediction results for two response variable from random forest
I use randomForest R package to do regression ...
2
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0answers
256 views
Prediction with CI - predict.glm doesn't have interval option
I have a model and a graph:
n1 = glm(formula = cbind(ml, ad) ~ x1, family = "quasibinomial")
plot(x1, ml/(ml+ad))
And I would like to plot a predicted line with ...
0
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2answers
228 views
Predicting time series with NNs: should the data set be shuffled?
Suppose I'm trying to predict time series with a neural network. The data set is created from a single column of temporal data, where the inputs of each pattern are ...
4
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0answers
162 views
Had statisticians predicted 2008 financial crisis?
Are there any statistical or econometric studies before 2008 that predicted 2008 financial crisis?
Note that there are some publications that attemp to predict contagion between markets using copula ...
4
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2answers
203 views
How to add confidence intervals to predicted data when the response variable is log transformed
I'm trying to predict the impact of avg grasshopper density(ghavg) on plant biomass. Both the response and predictor are continuous data. I had to log transform biomass (logmass) for a normal ...
1
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1answer
61 views
How to make inferences about a group based on test scores?
I have two datasets:
I have an exam score (pretend is the GRE) for all students that took the exam from 2000-2005, although I do not have student's private information (names, id,etc) I several ...
1
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1answer
197 views
Using multinomial regression's coefficients to derive predicted outcomes in C#
I am attempting to use C# (and the alglib library) to calculate the predicted probability that an outcome ends up in one of five classes. I have managed to calculate parameter estimates (i.e. slope ...
0
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1answer
201 views
still trying in R with CI and predictions
I looked over the tutorial in R for prediction and decided to reword my question.
I need the prediction on average for male with a 95%CI then repeat with maximal values using the variables status, ...
1
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1answer
110 views
How to get prediction intervals at mean & at max of covariate values in R
I'm still working on R problems from a book, and using my spending data.
Part 1: I need to predict the amount that a male with average data for status, income and verbal would spend along a 95% CI. ...
1
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1answer
81 views
learning R-understanding calculations for specific variable [closed]
Clarify why the prediction for a female in the example below in related topics (taken from a question by @MsSnowy) do we use the new calculations and not the original lm:
...
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0answers
135 views
Appropriate analysis for daily measurements
I have a data set containing a daily measurement recorded from 20 participants for 60 days.
I am trying to develop methods for predicting/estimating decline in
long-term monitoring studies, i.e. can ...
2
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1answer
237 views
Regression model with categorical values [duplicate]
Possible Duplicate:
How to test the statistical significance for categorical variable in linear regression?
As we know we can use linear models for numeric dataset(independent variables are ...
1
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1answer
154 views
Inaccurate R prediction
After development of recommendation engine with the R, before removal of outliers from data-set value of residual standard error was 1351 and after removal of outlier its 656. Still there is no ...
4
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2answers
575 views
How to predict or extend regression lines in ggplot2?
I have a data frame that contains two time series: the dates and version numbers of Emacs and Firefox releases. Using one ggplot2 command it's easy to make a chart that uses loess (in a way that looks ...
4
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2answers
71 views
Frequentist performance of sequential testing based on predictive power
Suppose we perform a hypothesis test from a random sample $(x_i)_{i=1}^n$, assuming for instance $x_i \sim_{\text{iid}} {\cal N}(\theta, 1)$ and $H_0=\{\theta=0\}$ for simplicity. If the test fails to ...
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5answers
1k views
Prediction in Cox regression
I am doing a multivariate Cox regression, I have my significant independent variables and beta values. The model fits to my data very well.
Now, I would like to use my model and predict the survival ...
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0answers
70 views
Determining which theoretical prediction is more in line with actual data
I have a question concerning the analysis of experimental data.
Imagine the following situation (which I simplify to make the point clearer):
I ask my participants to give a numerical answer to 3 ...
4
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2answers
378 views
Nested logistic regression in R
I am trying to find a way to do Nested Logistic Regression in R that fits my needs. I have a very large data set with almost 200 variables available. I have found my "best" model and it contains 12 ...
5
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0answers
162 views
Calculating prediction intervals when using cross validation
Are standard deviation estimates calculated via:
$
s_N = \sqrt{\frac{1}{N} \sum_{i=1}^N (x_i - \overline{x})^2}.
$
(http://en.wikipedia.org/wiki/Standard_deviation#Sample_standard_deviation)
for ...
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0answers
64 views
Prediction using dynlm/dyn [closed]
I was wondering if anyone could help me to carry out prediction using a dynlm model. I seem to have trouble as there are two lagged components within the model.
The model I've fitted is:
...
6
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1answer
681 views
Interpretation of simple predictions to odds ratios in logistic regression
I'm somewhat new to using logistic regression, and a bit confused by a discrepancy between my interpretations of the following values which I thought would be the same:
exponentiated beta values
...
2
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1answer
340 views
Can I get predictions from Winbugs/OpenBUGS?
I am new to WinBUGS and OpenBUGS.
I just fit a model to try an example. I was wondering whether I can get predictions generated by WinBUGS/OpenBUGS. If not, are there any convenient ways available ...
0
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1answer
108 views
Estimating maximum predictive power in noisy data
When assessing model performance, one would like to separate prediction errors due to limitations of the model from those errors due to intrinsic noise. For example, in noisy data, AUC in an ROC ...
4
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0answers
40 views
Estimating a time frame for interventions or judging the extent to which events become “determined” as time goes on
In certain arenas, it's valuable to be able to intervene early on to prevent problems from getting worse, because after a certain point there's not much you can do. Two examples might be public health ...
0
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0answers
160 views
How to display predicted probability for lmer objects with cubic splines?
I have fitted the following model:
fitmixed2 <-lmer(Type~rcs(Pt.Age,3)+rcs(Time.min,3)+Pt.Gender+ASA+School+(1|provider.id))
and thought I could use the ...
1
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1answer
115 views
Average weighted to exclude a predictor variable?
I have over 200 datapoints in my set and I have related my predictors (mostly categorical) to a single continuous response variable in a multiple regression model. The model is to my satisfaction, and ...
2
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0answers
43 views
Predicting the impact of increased seminar frequency
I'm working on an ongoing data analysis project about a series of live educational seminars. Each of my data points represents one such event, and for each one I have a multitude of categorical ...
3
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1answer
135 views
When do I need a model?
Considering the scenarios of exploring data, predicting (in the range of predictors), extrapolating and explaining- for which would one need a model? When can one do without one?
[Edit] By "model" I ...
6
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2answers
324 views
Estimating prediction error
Would appreciate any answer on characterizing/estimating prediction error on future data for nonlinear regression problem. Under what conditions would cross validation error or simple test error on ...
1
vote
1answer
104 views
Motifs for prediction
I'm trying to find a method for using motifs for prediction. Motifs defined as similar (sub)sequences can be found using approximate or exact methods, see Exact Discovery of Time Series Motifs.
My ...
2
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1answer
105 views
What will be/how do I estimate US household income in 2020?
I would like to know what US household income will be in 2020 by age group (eg. 15-34,35-44,45-54,65+). The US Census provides a historical Excel sheet ...
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3answers
374 views
Does the non-normality matter in using regression for prediction?
Does the non-normality matter in using regression for prediction?
Hi all,
In the QQ plot of the residuals after linear regression, the residuals turned out to be highly non-Gaussian.
Most of the ...
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2answers
290 views
Impact of regression normality-assumption on model comparison & prediction?
This question is a continuation of the discussion here:
How to test the statistical significance for categorical variable in linear regression?
Following Macro's suggestion, I started a new thread.
...
3
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1answer
290 views
Basic Multivariate Regression Analysis with R
I'm trying to look for simple patterns in weather data. Here's a simplified version of what I'm working with.
...
5
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1answer
597 views
How to get prediction for a specific variable in WinBUGS?
I am a new user of WinBUGS and have one question for your help. After running the following code, I got parameters of beta0 through ...
5
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3answers
378 views
Is it necessary to detrend and decycle time-series data when using machine learning methods?
For example:
I want to forecast future values of a time-series based on previous values of multiple time-series' using a ANN and/or SVM. Inputs will be lagged values from each time series, and the ...
2
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0answers
163 views
How do I predict performance for individuals who haven't taken any courses yet?
I'm trying to do a logistic regression on some data.
Here's a simplified version of the situation:
I'm trying to predict student success based on their history, etc. One of my predictors is the ...
1
vote
1answer
950 views
error in getting predictions from a lme object
I am trying to get predictions for observations from a lme object. This is
supposed to be quite straightforward. Yet, since I am get different types of errors for different trials, it seems to me I ...
2
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2answers
185 views
Estimating good buying and selling prices on eBay using eBay sales history
I am trying to create the algorithm that will tell me the good price to buy stuff and a correct re-selling price based on eBay item history.
The main variables would be the auction type (buy now or ...
4
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2answers
202 views
How to judge if a datapoint deviates substantially from the norm
This is statistics 101, but I'm not a statistician and so can't seem to find the right technical jargon to google.
My company collects data at discreet points through time. Today's datapoint is ...
0
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1answer
166 views
Significant predictor loses significance when second non-significant predictor is entered (log regression) [duplicate]
Possible Duplicate:
How can adding a 2nd IV make the 1st IV significant?
I am looking at the prediction of relapse by gender.
In a hierarchical log regression, with gender entered in first ...
1
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0answers
97 views
Alternative measures of prediction power?
What are alternative measures of the prediction power of a model, apart from the coefficient of determination $R^2$? What are their strengths and weaknesses, especially in comparison to the $R^2$?
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3answers
204 views
Choosing a null hypothesis to answer the question “Are my model's predictions better than random?”
I'm currently trying to evaluate a model of metabolism which aims to predict whether deleting individual genes will cause a growth defect (there are ~850 genes in total). I know from experimental data ...
6
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1answer
476 views
ABC model selection
It has been shown that ABC model choice using Bayes factors is not to be recommended due to the presence of an error coming from the use of summary statistics. The conclusion in this paper relies on ...
