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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error function in linear regression [duplicate]

In linear regression squared error function is calculated as: error = Sum (WTxi -yi) In which "Sum" means summation of (i=1 to m (m is number of samples.). WT ...
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Asymmetric regression (assymettric loss for regression)

I have a hybrid classification/regression problem. The predicted value can be assumed to be centred around 0. I want to penalize the predictor more, if the predicted value and actual value have ...
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Linear regression with estimates of error in predictor

I have data with two different kinds of measurements at the same set of $S$ sites. One of these (call it $X$) returns m estimates at each site, which are not necessarily independent of one another. So ...
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8 views

Linear Regression and error calculation with streaming data [on hold]

How to calculate error when perform linear regression if data is in streaming pattern ?
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troubleshooting R BayesFactor package - error in regressionBF [on hold]

I want to use regressionBF to run all subsets regression. Here is my code: fitness.bf = regressionBF(VO2 ~ ., data=fitnessdata) and here is the error it spits out when I try and run the code: Error ...
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When to use non-additive stochastic error term

I have encountered the following two versions of the Cobb-Douglas production function as an illustration of the differences between intrinsically non-linear and linearisable non-linear regression ...
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Are cross-validated prediction errors i.i.d?

Say, we test an arbitrary regression or classification procedure on $n$ independent samples with leave-one-out cross-validation. This results in an estimate of the prediction error $e_n$ for each ...
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Do I have a correct understanding of Margin of Error/Accepted Error involved in sampling - Conflicting Previous Answers

I constructed a sample size calculator in Excel: Response Rate * (1 - Response Rate) * [Norm.Inv((1-alpha)/2) * (-1)/Accepted Error]^2 If post sampling I have: p ...
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Is there any statistical basis to relative error?

Given a true value $b$ and an approximated value $a$, Wikipedia defines the absolute error to be $\lvert a-b \rvert$ and the relative error $\left\lvert\frac{a-b}{b}\right\rvert$. Ensuring that the ...
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What is the difference between errors and residuals?

While these two ubiquitous terms are often used synonymously, there sometimes seems to be a distinction. Is there indeed a difference, or are they exactly synonymous?
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Errors on a regression line [duplicate]

This may have a simple answer but google has failed me so far. How do I calculate the error on the slope and y intercept of a regression line, which takes account of the errors on each data point? ...
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8 views

Error propagation through convolution

I have a list of data points $y_i$ and a respective uncertainty $\sigma_i$ associated to them. Now I am convoluting this with a Gaussian window function (discretized $w_i$) "numpy.convolve" function ...
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Is the ALRE method of standardization/rescaling appropriate for proportion data?

I have data in which groups of experts make proportion estimates. I've been encouraged to use the ALRE method of scoring the error of these estimates. I found an article which describes this method: ...
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Mean Absolute Scaled Error

Right now, I am analyzing the prediction quality of a dynamic model that has variables with different units (e.g. $x_{1,t}$ is in meters, $x_{2,t}$ is in kilograms etc.). I have discovered a great ...
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31 views

Relative Error Temperature

I have a model to simulate temperatures and I want to compare it to reference values. I thought that the relative error (or rather percentage error) would be interesting, but I'm rather confused on ...
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2answers
55 views

Is covariance between two dummy variables zero?

Here is a problem I am facing: I need to test a hypothesis (t test), the formula for which is $t = \frac{\hat{B_1} - \hat{B_2}}{se(\hat{B_1} -\hat{B_2})}$ Now, we know that the bottom isnt actually ...
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Are data handling errors already 'priced in' to statistical analysis?

Ok, fair warning--this is a philosophical question that involves no numbers. I've been thinking a lot about how errors creep into data sets over time and how that should be treated by analysts--or if ...
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What's the difference between error distribution and residual distribution in generalized linear models?

I have met with generalized linear model, but I'm confused with the errors and residuals? Can anyone help me out? I have got three questions. (1)what's the difference between error and residual? ...
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42 views

Matrix Inversion Error

I a Multiple linear regression model, from published literature, I am implementing a spreadsheet to generate new predictions based on the published model. the literature stated Coefficients and the ...
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114 views

Understanding the error term

I am trying to figure out the meaning of these different "hatted" terms in regression analysis. Here is my basic understanding: $Y$ the original of population/sample values $\hat{Y}$ regression ...
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28 views

propagation of the error in the summation

I have a question regarding the propagation of the error during the summation. Please see the equation below. In this equation only quantity R has an error. How it will propagate to the final value ...
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8 views

What is the test error, if response in test set is missing?

I am given two data set: one used for train model, and one for prediction. However, there is no response variable in the second data. I was asked to test the model built from the first data on second ...
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7 views

Fit vertices to minimize Error when linearly interpolating

For a curve like the one below: Given that we have a certain amount of vertices for approximation, say 5. How to find appropriate x values to place the vetices on ...
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Are there closed-form expressions providing the VC-dimension for the multi-class case for different classifiers?

So far, I've only encountered the VC-dim for binary classifiers. I'm interested to know how this notion can be extended to the multi-class case. Are there expressions that provide bounds on the ...
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54 views

Square root of number of counts vs standard deviation of the mean?

I'm doing an experiment in radioactivity, where I measure the number of counts in a given time interval when a radioactive source is placed in front of a detector at a fixed distance. I repeat 3 times ...
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68 views

Can Chebyshev inequality be used to bound the error of the sample mean?

Can the probability of error of the sample mean, i.e., $\Pr(|\bar{X}-E[X]| \geq \epsilon)$, be bounded using Chebyshev inequality (or something similar)? $X$ is a discrete random variable with an ...
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Choosing between two parameters based on the mean and the standard deviation of the error

I am trying to interpolate data under the assumption that I have the true data. The interpolated data is dependent on a parameter which I am trying to estimate. For each possible value of this ...
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28 views

Can One Compare the Margin of Error of a 7-point Likert Scale vs 9- point Likert Scale

In many of our product tests and attitudinal studies where we ask for rating on Overall Liking (a product), product managers either use a Likert scale of 7 or 9-points with each point anchored (ex. 7= ...
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Distribution of Standard Deviation of 2 Variable Linear Regression

Assuming we have a fit: $\hat Y= \alpha + \beta (X-\bar X)$ Such that: $Y_i=\alpha+\beta(X_i-\bar X)+\varepsilon$ The standard deviation of $\varepsilon$ is $\sigma$. Estimated in an unbiased way ...
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Experimental Design questions

I have a couple of questions regarding the procedures in an experiment. If I would like to test out two different drugs and the effect it has on the subject, why would it be a good idea to randomize ...
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Error Propagation

I come from a physics background where the only error propagation I've dealt with was in the lab using the simple formulas found here: ...
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19 views

A proper error-of-fit measure to evaluate log-linear model prediction?

I want to evaluate predictions from a log-linear model. Because the response variable (y) varies over several orders of magnitude, standard measures like RMSE or ...
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1answer
24 views

Can I take the mean of an indirect measurement?

I've been told that one shouldn't take the mean of indirect variables. Specially, I should not give the standard error as the error of the mean. To give an example, if I'm using Ohm's law $V=RI$ and ...
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What is Median Error Distance and how to calucalte it

How to calculate Median Error Distance? I'm looking at "Schulz A. et al. A Multi-Indicator Approach for Geolocalization of Tweets". They are calculating Median Error Distance. But how they are do ...
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cvFit mean predicted error interpretation for nls models

I have been using the cvFit() function of the cvTools library in order to test my models (nls() ones), but I would like to know more precisely what the cvFit() returns to me when it's done. It only ...
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59 views

How to measure when error stabilizes (convergence) on Random Forests (or, when do I stop training)

I'm doing an implementation of Random Forests. As I was the original paper (page 11) and this nice book on the subject (15.3.1, page 592), they mention that when the out-of-bags error stabilizes (when ...
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1answer
77 views

Undefined real result error at WinBUGS

I am currently working on my thesis and interested in estimating a multilevel differential item functioning model and I using at WinBUGS. Until I had done model check-up, there are no errors. However, ...
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Standard error notation

Dealing with a standard error of a mean $$ \widehat{SE}_{\bar x} = \hat \sigma_{\bar x} = \frac{s_x}{\sqrt{n}}$$ $$ SE_{\bar x} = \sigma_{\bar x} = \frac{\sigma_x}{\sqrt{n}}$$ Is this the ...
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How to include the error term as an explanatory variable in a lm() model when the errors are auto-correlated?

I am wondering if there is a way to include the error term as an explanatory variable in a lm() model when the errors are auto-correlated. For example, I have a model that gives errors that has a ...
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16 views

Standard error of the mean for binomial dist [duplicate]

I know what intuitively what's going on but... We know that in general the standard error of the mean is $$ \sigma_\bar{X}^2 = \sigma_X^2/n $$ Right? But when I apply this to the binomial ...
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Standard Deviation expressed in percentage

I did an estimation. I got the result, lets call it x. Then, I did the experiment. I got another result, y. I need to know what difference in percentage is between those 2 results? What is the error ...
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63 views

Selecting priors based on measurement error

How do you calculate the appropriate prior if you have the measurement error of an instrument? This paragraph is from Cressie's book "Statistics for Spatio-Temporal Data": It is often the case ...
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1answer
38 views

Use of infinity norm instead of SSE for machine learning accuracy?

Are there any examples or arguments in favor of using an infinity norm (or equivalent) over sum of squared errors or root mean squared error for evaluating machine learning algorithms?
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How do you scale percentage intervals based on absolute size?

If you were told the travel time from A to B is 5 minutes, you wouldn't mind if it took between 0 and 10 minutes. So happy within 100% of 5 minutes. If the trip took 5 hours (360min), you wouldn't ...
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21 views

What is the relationship between separable SVM test error bounds and soft-margin SVM test error bounds?

Can I compute the bounds for a soft margin SVM by taking the VC dimension for an SVM and using the misclassified examples as train error? Does the inequality from wikipedia's VC dimension page hold ...
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13 views

logarithmic calibration and geometric mean - citation search

I have a logarithmic calibration line: MachineSignal = -3.21 log(concentration) + 21.9 It seems obvious to me, that if I have a triplicate measurement of concentrations (measured indirectly through ...
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How to calculate MoE for subsamples

I have demographic and income data for 3 million people from the American Community Survey (courtesy of IPUMS), and my goal is calculate the median income for every permutation of age group, gender, ...
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1answer
137 views

Error bars and coefficient computation on linear regressions in Matlab

I have a handful (~5) of values x I need to plot against a handful of values y (actually, log(x) vs. log(y)), in order to derive a linear equation used to derive an empiric power equation. However, I ...
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Error of bounded mean estimation with quantization

I have a distribution whose mean $\theta \in [0,1]$. Given $n$ observations, I compute the sample mean (say $\hat{\theta}$) and quantize it to accuracy $\frac{1}{n}$ (basically I can use only ...
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26 views

Is margin of error truly valid at extreme proportions? Such as 1% agreement, mere traces of data

Survey margin of error contracts as the proportions become more extreme. Its validity and applicability in such cases has always concerned me, but I suppose much depends on the context. Where we have ...