The error tag has no wiki summary.
0
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0answers
29 views
How to prove $H(X-Y)\le \log(2\pi eD)$?
In rate distortion theory, difference error entropy $H(X-Y)\le \log(2\pi eD)$, how can we prove this?
0
votes
0answers
24 views
Lognormal and Logit models in JAGS
I'm trying to run this two-part model in JAGS. I have two components, one logit and one lognormal regressions in there:
...
2
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0answers
26 views
Correlated error term residual in logit regression what are my options?
I have estimated a model, with many interactions of both continuous and factor explanatory variables, which is to be used for prediction.
My model has performed reasonably in out of sample testing.
...
-1
votes
1answer
43 views
Error message of ugarchfit? [closed]
I try to fit an ARMA-GARCH process to my data. I use the rugarch package
The mean equation should be "nothing", so no Ar no MA and no intercept.
The volatility equation should be equal to ...
0
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0answers
36 views
Standard deviation of errors
I have a multiple regression model (information derived from gretl):
$$Y=‐3,859921 \ln(P)
+
1,707514\,
(A)
+
3,578656$$
$$\quad\quad\space(1,216387)\quad\quad\quad(1,259650)\quad\quad(0,323867)$$
...
0
votes
0answers
22 views
website performance measurement error
I have 2 measurements from my website performance measurement tool ( 6 months data with 12 points per day). Both have some error as one of them is overestimating the response time and one is ...
1
vote
1answer
134 views
1sigma error on the mean
My x and y data (n) have a non normal distribution. I'm measuring the mean of the distribution (I'm using Python):
x_m=np.mean(x)
y_m=np.mean(y)
I would like to ...
1
vote
3answers
71 views
Truncating error bars in publication graph?
I am preparing a graph for publication: it has 3 panels, and two groups (line graphs) in each panel, with error bars at each time point.
For one of the panels, the last time point (with fewer ...
3
votes
2answers
137 views
What are good RMSE values?
Suppose I have some dataset. I perform some regression on it. I have a separate test dataset. I test the regression on this set. Find the RMSE on the test data. How should I conclude that my learning ...
1
vote
0answers
31 views
Accuracy Measurement in Biased Dataset
Lets say we have data-set consists of 100 instance, each instance belong to one of 6 classes {1,2,3,4,5,6}. Furthermore, 70% of the instances belong to class 3.
For classification problem, if the ...
0
votes
0answers
40 views
dudi.pca error in v*row.w: non-numeric argument to binary operator
I need to run a dudi.pca from the package ade4. I am running it on a species dataframe with the 1st column as ...
0
votes
0answers
55 views
JAGS error when fitting logistic additive mixed model
I have longitudinal data, where there is a binary outcome variable. There are 1 to 6 repeated observations per subject. One of the predictor variable is numerical. All the other predictor variables ...
1
vote
0answers
11 views
Efficent global minimum search of costly to evaluate low dimensional error function
Trying to minimize the error from a probabilistic regression model which is composed of hierarchical KDE estimated PDFs. The top level is the result of 2-4 separate meta-PDFs from different data ...
0
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0answers
59 views
Finding the projection used in multidimensional scaling
Background
I have a set of data points in high-dimensional (512D) space that I wish to map to 2D for visualisation. I am interested in observing in 2D the (approximate) relative distances between the ...
0
votes
0answers
83 views
How does Newey-West covariance help increase accuracy of OLS estimates?
I have implemented a model using OLS estimates, but the results don't look too good. I've come across this term 'Newey-West covariance', and that I need to use residuals from my model as input, but ...
1
vote
1answer
157 views
Estimate error of prediction from R-square
What I have:
a linear model $y=a_0+a_1x$ with given parameter estimates,
the number of values used for fitting the model,
the Pearson R² value.
I need to estimate errors of prediction. I don't see ...
0
votes
0answers
28 views
Relationship between threshold, number of features and accuracy/error? (text classification)
Are you aware of any research papers that explain a relationship between the following concepts?
threshold (removal of features, whose frequencies are greater than or less than a defined ...
3
votes
0answers
61 views
Error Bars for Peaks in Noisy Data
I'm doing an experiment where peaks in amplitude $A$ (the dependent variable) are expected as one varies the frequency $f$ (the independent variable).
Based on our theoretical model,
Away from the ...
1
vote
1answer
101 views
Propagation of uncertainty through an average
I have a set of distance measurements that are all accurate to +/- 0.01 M.
{1.00,2.00,3,00}
We can obtain the distance moved ...
1
vote
0answers
36 views
Compare measure vs. true value: Methods and Visualization
I have a simulation routine that produces measurements of a continuous variable and I also know the true value. What is the optimal method to graphically depict, analyse and present the error or ...
0
votes
1answer
90 views
0
votes
1answer
101 views
Sum of Squares reference resources
I am trying to really understand Sum of Squares, but what I read is either the summation formula for each one or answers like this.
Could some one point me towards a good reference that gives a bit ...
1
vote
1answer
45 views
Remove for systematic error (ANOVA)
Having a systematic 'error' (due to a 3 leveled external/experimental factor) influencing the variable I want to predict with my model.
How do I best find a sound model that represents the underlying ...
1
vote
1answer
53 views
Error Propagation and Under-represented Variable
I am running a relatively simply propagation of error analysis on an equation:
$$S = \frac{ABC}{XY}$$
I have independent random error terms calculated for each variable (for the purposes of this ...
1
vote
1answer
63 views
With regards to asymettric error bars, what is the correct alternative to S.E.M. when data are strictly positive and near zero?
I have some data that measures how a substance decays over time. At each time point I have 4 measurements. At time points where there is a lot of substance I use the standard error for error bars and ...
0
votes
0answers
95 views
I don't know how should I calculate meaningful error bars in this special case
I have 6 masses as input data which they are expressed as m+/- delta m.
Via a complicated processes I calculate decay width as a final result.
It takes a long time for the code to compute decay width ...
8
votes
3answers
714 views
Number of significant digits to report
Is there a more scientific way of determining the number of significant digits to report for a mean or a confidence interval in a situation which is fairly standard - e.g. first year class at college.
...
1
vote
2answers
160 views
Mean square error of classification
I know the mean square error formula and how to compute it. When we talk about a regression we can compute the mean square error. However can we talk about a MSE for a classification problem and how ...
-2
votes
3answers
300 views
Adding noise to a matrix/vector
How to add noise to an object, regardless of the amount of dimensions?
I would expect to try to use some sort of apply to add noise of the type:
...
6
votes
2answers
418 views
Why use a certain measure of forecast error (e.g. MAD) as opposed to another (e.g. MSE)?
MAD = Mean Absolute Deviation
MSE = Mean Squared Error
I've seen suggestions from various places that MSE is used despite some undesirable qualities (e.g. http://www.stat.nus.edu.sg/~staxyc/T12.pdf, ...
1
vote
1answer
132 views
Different types of error rates when there are multiple comparisons
I have seen 5 different type of error rates. They include:
Componentwise Error Rate
Experimentwise Error Rate
False Discovery Rate
Strong Familywise Error Rate
Simultaneous Confidence Intervals
...
0
votes
1answer
63 views
How to evaluate a curve considering outliers?
I have data on runners who run marathons; for each runner I have their final times on a number of races. I would like to predict how fast they are running considering outliers i.e.
he's running ...
0
votes
0answers
85 views
Descriptive statistics in a repeated measures study
I'm doing a retrospective study looking at how the mortality of piglets differs with increasing age of pigs.
Since my data is for each sow over seven years and each sow may only have mortality in ...
1
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0answers
30 views
Probability of x given past data and linear model assumption
I have a set of data where for every new point $x$ I need to know how probable this point was, given the past data.
I can assume the data follows a linear model.
I know I can find a simple linear ...
0
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0answers
77 views
What is Generalization errror on training set. How can I see it on weka?
I get output like this ..
...
1
vote
2answers
191 views
5
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2answers
124 views
Quantile regression and heteroscedasticity/autocorrelation
I hear it said [1] that QR makes no distribution assumptions about its error term.
Question 1: Does this mean that heteroscedastic and serially correlated disturbances do not effect the ...
0
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0answers
47 views
When correlation coefficient's value rises, error rises as well. Is this normal behaviour?
So here's a question. lets say we have three datasets A, B, C, D(continuous, that take values within the data range [0, 5]) where C and D are actually the predicted values of A and B accordingly, ...
2
votes
1answer
872 views
RMSE vs. Coefficient of Determination
I am evaluating a physical model and would like to know which one of the methods I should be using here (between RMSE and Coefficient of Determination R2)
The problem is as follows: I have a function ...
11
votes
2answers
250 views
How to design and implement an asymmetric loss function for regression?
Problem
In regression one usually computes the mean squared error (MSE) for a sample:
$$
\text{MSE} = \frac{1}{n} \sum_{i=1}^n\left(g(x_i) - \widehat{g}(x_i)\right)^2
$$
to measure the quality of a ...
2
votes
0answers
81 views
What is the relationship between 10-fold CV RMSE and test set RMSE score?
In my opinion, these two RMSEs are proportion related. I use the training set to get 10-fold CV RMSE and get a model on the whole training set to predict on the test set. As the training set is larger ...
0
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0answers
37 views
Is there an extension of the James-Stein estimator for cases of nondiagonal covariance matrix?
Is there an extension of the James-Stein estimator for cases of nondiagonal covariance matrix?
James-Stein estimator holds for every multivariate distribution but are there any improved versions ...
0
votes
1answer
71 views
What is the error here?
Consider the following:
Researchers conducted two different types of test on a large group of people. After that, the researchers subjected the people to situations like Z and noted their response R. ...
3
votes
0answers
94 views
Error bars for L2 regularization?
Is there anyway to describe them? I'm a bit new to the field, and a problem I'm working on has led me here. Some background:
Given X and B, find A that minimizes
$$
\text{argmin}(A) || AX - B ||
...
10
votes
1answer
102 views
Correcting for normally distributed clock inprecision
I have an experiment which is executed on hundreds of computers distributed all over the world that measures the occurences of certain events. The events each depend on one another so I can order them ...
1
vote
1answer
82 views
Error on weighted mean
I have some measured datapoints. Each of the points has attached an error, depending on how precise the measurement was done.
Now I'm using the squared weighted mean with the inverse of the errors as ...
2
votes
1answer
106 views
Measuring error in the lag when cross-correlating data
Cross-correlation can be used to measure a 'lag' (or shift or offset) between two data sets (e.g., data streams). Is there a standard way to measure the errors in the 'lag'? Or better yet, is there ...
0
votes
1answer
74 views
Question on sampling error
I have problem understanding following example in parentheses. Maybe you can help me.
Ideally, researchers know the full extent of the population they want to study, and they can select a sample from ...
6
votes
3answers
420 views
How to choose an error metric when evaluating a classifier?
I've seen different error metrics used in the Kaggle competitions: RMS, mean-square, AUC, amongst others. What's the general rule of thumb on choosing an error metric, i.e. how do you know which error ...
3
votes
1answer
324 views
RMSE vs MAE when dependent variable is between 0-1
I am comparing error estimates from different models. I am looking at MAE (mean absolute error) and RMSE (root mean squared error) as my choice of error estimates.
But the problem is that mostly they ...
