The error of an observed value is the deviation of the observed value from the (unobservable) true function value. Do NOT use this tag for SOFTWARE ERROR messages.

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125 views

Error term in linear regression

I'm reading about a linear model which is fit to an equation, $Y = \beta_0 + \beta_1X + \varepsilon$, where $B_0$ is the intercept, $B_1$ the slope, and $\varepsilon$ the error term. My question is, ...
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1answer
17 views

Standard Error for Weighted Values

I want to calculate the standard error for an experimental measurement. The data is stored as a 2D image which is circularly symmetric about a center point. To reduce the data we radially integrate ...
0
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0answers
18 views

Factor Analysis - Rotated Component Matrix Error

I haven't got good English but i have a problem: (for my master thesis.) I did factor analysis, deleted 4 questions and the most lower points are: ,392 and ,393. So, i go on and deleted 0,392 ...
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0answers
20 views

How can we calculate the standard deviation of multiple values with different uncertainties each?

For example, if I have a set of readings, like: 13.4 +/- 0.5 14.5 +/- 0.7 12.8 +/- 0.6 13.9 +/- 0.4 14.8 +/- 0.5 How do I calculate the standard deviation of ...
0
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0answers
20 views

Model Error bars

I have actual observations and estimates from a model (power-law fit). I want to add error bars (+-1 Standard Deviation) to the estimated points. I tried excel and R, but I am not able to calculate ...
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0answers
8 views

Getting warnings when running VGAM package in R?

Here is part of the code I'm running in R after loading the RODBC, VGAM, and Matrix ...
0
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1answer
23 views

Is there any error metric like accuracy (the percentage) for regression model assessment?

Is there any error metric like accuracy (the percentage or the misclassification rate) for regression model assessment? since the percentage shows more directly how the model performance is. ...
1
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0answers
25 views

Error of the variance

I have a collection of $(x,y,z)$ data points. I want to compute the mean, $\mu$, and variance, $\sigma^2$, along each axis, as well as the errors on each. I know that the standard error of the mean ...
0
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1answer
20 views

Statistic test when bias is not random

Is there a statistical test that I can use to say that there is bias in the result of my analysis but the bias only occurs at certain region. The scatter plot below probably will make more sense: ...
0
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0answers
25 views

P value validity

I have done a statistical analysis in DNA methylation data, I already wrote my report, but it got rejected by my adviser as he wants me to do some changes in the paper. One question I couldn't answer ...
0
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0answers
22 views

Diagnosing Unusually High Prediction Accuracy in Logistic Regression Model

I have constructed a logistic regression classifier in Matlab, using all self-written code. The data set I decided to use is the Breast-Cancer data set from UCI's machine learning repository. This ...
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0answers
21 views

RMSE and Decision Trees

I'm running a series of regressions using decision trees and am getting good results, but I've got a question. In the pacakge rpart, you can run cpplot to get a graphical representation of where to ...
0
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0answers
6 views

Error term Moving average

How do we find theoretically the error terms for each observation and parameter values in case of Moving Average model? Eg- if we have data set like--- 500,512,508,519 then how do we find error terms ...
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0answers
13 views

Neural networks kernel for high error rate in training set.

I will be working with a huge training set (around 10^6 examples, with around 400 features). Which has labels (around 100) accurate to around 90%. It would be possible to generate a smaller subset of ...
-1
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2answers
17 views

Finding the error terms in regression equations

In a regression equation that one has to show as e.g. y=(1.20+-0.02)+(5.61+-0.04)x for publication, how does one determine the error terms? Sometimes they are also different, as in ...
1
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1answer
37 views

Prediction uncertainty intervals for predictions of machine learning algorithms

Assume I have a regression problem. I fit models on a train data set and tune their hyperparameters using CV. I then run the models on the test set. What is the best way to calculate prediction ...
0
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0answers
50 views

How to check if a sample is representative or not biased?

We are studying the difference in behavior between genders on an online community. We are only interested on those users who participate in the site and whose gender could be easily inferred by other ...
0
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0answers
23 views

Checking error in optimisation problem

My apologies if this problem is trivial -- I do not have much experience with statistical methods! Hopefully someone can point me in the right direction. Background: I am currently working on an ...
0
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1answer
26 views

Estimating errors for parameters from a nonlinear fitting procedure

I'm examining a code in C++ for a nonlinear fit. It is basically a Levenberg Marquardt routine you can find on Netlib or elsewhere. The last step is estimating the errors of the parameters that are ...
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0answers
13 views

NMSE - division by zero

I am using the normalized mean square error function in the Python Oger Toolbox which is defined as: ...
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0answers
12 views

Variance matrix for model errors

I am having trouble with understanding how can I write out the variance matrix for model residuals. I have a very simple data with 6 observations: ...
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0answers
16 views

measurement error from self reported data

The point is to investigate effect of school enrolment on cognitive development. Suppose formal enrollment is self reported by the student. How would measurement error affect estimate of enrollment on ...
21
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5answers
1k views

Is minimizing squared error equivalent to minimizing absolute error? Why squared error is more popular than the latter?

When we conduct linear regression $y=ax+b$ to fit a bunch of data points $(x_1,y_1),(x_2,y_2),...,(x_n,y_n)$, the classic approach minimizes the squared error. I have long been puzzled by a question ...
0
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0answers
14 views

Error term in anova

There is an example on this page (last part): http://www.personal.psu.edu/mar36/stat_461/split_plot/split_plot.html Rats were fed with different diets after which glycogen in their livers was ...
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11 views

question about deviation and error %

I was conducting an experiment where an indicated temperature on a sensor read -0.2 degree C. But the same temperature on a thermometer read 0.0 degree C. The deviation is equal to 0.2. And the error ...
5
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1answer
80 views

Minimizing symmetric mean absolute percentage error (SMAPE)

I am working on a forecasting application in which forecast errors are measured using the symmetric mean absolute percentage error: $$ SMAPE = \frac{1}{n} \sum\limits_{t=1}^n{\frac{|F_t - A_t|}{F_t + ...
2
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2answers
162 views

How to add noise to a random variable whose range is the unit interval? [closed]

I have a list of values sampled from a beta distribution that therefore lie in the interval [0,1]. I would like to add (e.g. Gaussian) noise to these values, but of course there is the problem of the ...
1
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1answer
56 views

Errors vs measurement errors

I'm reading about how to fit a straight line with measurement errors in both coordinates ($x$ and $y$). Let the true unobserved variables be $x_{t,i}$ and $y_{t,i}$ and the observed variables be ...
0
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0answers
23 views

Is it okay to use relative error on a set of measurements rather than an absolute error?

As far as I've learned, if you have a set of measurements and the differences between the average of those measurements and the individual measurements aren't always smaller than the absolute error of ...
1
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2answers
86 views

Why don't we train neural networks to maximize linear correlation instead of error?

Recently a project I've been a part of has involved training neural networks so that we maximize the Pearson correlation between actual and predicted values. So this came to my mind: why don't we ...
2
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1answer
19 views

Non neglible instrument error associated with a mean

I have N samples, that have mean X and standard deviation sigma. So far so good. I know that each sample has been measured with a measurement error e. Because the data is real world data the ...
2
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0answers
28 views

Ratio “observed-to-expected” - how do you call it?

Is there a name for the ratio of the observed count in a cell (say, ij) to the expected count in it - $O_{ij}/E_{ij}$? Likelihood ratio Chi-square (= G-square) statistic is based on these quantities. ...
2
votes
1answer
30 views

GLM with Gamma distribution of errors: negative residuals?

I'm trying to understand how the Gamma distribution, which is always positive, is used to describe errors when using a GLM. In practice, errors can be negative, as I get negative residuals when ...
3
votes
1answer
227 views

What's the difference between the variance and the mean squared error?

I'm surprised this hasn't been asked before, but I cannot find the question on stats.stackexchange. This is the formula to calculate the variance of a normally distributed sample: $$\frac{\sum(X - ...
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28 views
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0answers
18 views

How do you report percent error with limited precision?

Let's say you have an experimental data point with limited precision, such as 0.67 ± 0.1, and a known actual value such as 0.72. What is the standard way to report the percent error in this case, ...
1
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2answers
45 views

error analysis on nonlinear curves

I have a set of data from a simulation that generates a curve, and I have a mathematical model (from theory) on what things are supposed to look like. Of course, there is some error expected between ...
0
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1answer
23 views

The probability of m out of K things being wrong with an error of ɛ

I have a homework question about a machine-learning algorithm that uses ensemble learning with simple majority voting. Assuming we have K hypotheses, each with an error ɛ, the question asks us to ...
3
votes
1answer
74 views

Should I use Mean Square Error or Classification Rate?

I am a self-taught person and I would like your help. I am learning about predictive modeling in general, and I'm also trying to do predictive modeling for a specific problem. I am exploring ...
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0answers
15 views

When is it appropriate to use the estimation of error bar $\sqrt{frequency}$?

I have some data which follows poisson distribution. I am just curious under what circumstances is the square root of the bin appropriate to use as an error bar? When do I get in trouble for using ...
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0answers
13 views

Choosing which distribution is most accurate

Let's say we have two samples from different normal distributions and we want to determine which distribution is most accurate relative to an ideal value. How would we evaluate which one is more ...
0
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0answers
26 views

Perceptron Algorithm, RMSE just cycles through two numbers

My input is a bag of words feature vector, of the form: Example: Document 1 = ["I", "am", "awesome"] Document 2 = ["I", "am", "great", "great"] Dictionary is: ...
4
votes
2answers
140 views

What does an error in ANOVA indicate?

When I came across ANOVA, the instructor talked about df(Error), ss(Error), etc. What do these error terms indicate? Do error terms differ for two-way ANOVA with dependent and independent variables? ...
1
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0answers
18 views

Question about relative percent error with widely varying expected values

I'm looking at a large collection of values. These values follow an exponential distribution. I have their probabilities and a pre-made Excel spreadsheet that will auto calculate expected values from ...
9
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1answer
286 views

Additive Error or Multiplicative Error?

I'm relatively new to statistics and would appreciate help understanding this better. In my field there is a commonly used model of the form: $$P_t = P_o(V_t)^\alpha$$ When people fit the model to ...
0
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0answers
48 views

When to use CRPS (Continuous Rank Probability Score)? What are the alternatives? What are the advantages and disadvantages?

Please correct me if I'm wrong, crps is new for me. I want to understand it better. We have to minimize crps, which is based on the cumulative distribution function of the data. While the information ...
0
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1answer
13 views

ESL: base error rate question

In page 51, of ESL, it says "The mean prediction error on the test data is 0.521. In contrast, prediction using the mean training value of lpsa has a test error of ...
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0answers
16 views

Learning to filter audio: Error falls near zero but output is always rubbish

I'm new to machine learning and I'm trying to train a neural network to separate audio from a mixed track. Training data I've collected a bunch of audio snippets from freesound.org, grouped by ...
0
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0answers
40 views

How to get the error and error variance after hierarchical bayes using bayesm

I estimated individual part-worth based on multiple paired comparisons by using Bayesian logistic regression in R (bayesm, model: rhierBinLogit by Rossi). rhierBinLogit implements an MCMC algorithm ...
4
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1answer
167 views

Reinterpreting a Poisson regression

The way I understand a Poisson regression is that we model $y|x \sim \text{Poisson}(\exp(x'\theta))$ so that $E[y|x]=\exp(x'\theta)$ (e.g. http://en.wikipedia.org/wiki/Poisson_regression). My ...