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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Percent error for linear regression model

Suppose I fit a linear regression $y = \beta x + \rm error$. In this situation, $x > 0$, $\alpha > 0$, and therefore $y > 0$. Moreover, the $\rm error$ is normally distributed with mean $0$ ...
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1answer
94 views

Do Beta weights from regression have error terms?

I am looking at standardized regression weights (i.e., Beta weights). I was thinking of reporting the errors next to the weights in a figure, but upon some thought I was debating whether such errors ...
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1answer
26 views

Unknown name of this test

I would like to know the exact name of a test for measuring the similarity of 2 noise systems. Assuming m1 being the measurement for system 1 and m2 the measurement for system 2 this test computes S1 ...
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1answer
20 views

Error Propagation Calculation

I have a few machines that are used to calibrate each other. Machine 1 has is accurate to 0.025% Machine 1 is used to calibrate Machine 2, which has an accuracy of 0.005% Machine 2 is used to ...
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15 views

How to convert numeric value to date format [migrated]

I imported .csv file containing a date in one field. But when I use mode() for that variable, it shows as numeric. My ...
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0answers
31 views

Neural Network Error Plot Odd Effect

I'm using R to fit a neural network to data generated by the formula $y = x^2 + \epsilon / 2$ where $x \sim \mathcal{U}(0, 2)$ and $\epsilon \sim N(0, 1)$ (very simple, right?). The following plot ...
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8 views

Error scores analysis

The research paper examines the reaction times on a task and incorrect answers are eliminated as errors. The study does not specify the analysis however report a result of ps > 0.1 . What statistical ...
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21 views

Expected prediction error - derivation

I am struggling to understand the derivation of the expected prediction error per below (ESL), especially on the derivation of 2.11 and 2.12 (conditioning, the step towards pointwise minimum). Any ...
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0answers
19 views

What difference (if any) exists between the Response Distribution and Error Distribution in GLMs?

Ok, forgive my ignorance, but I keep getting confused about something at the core of GLMs. Some textbooks describe the two main parts of a GLM as the link function and the distribution of the error ...
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1answer
22 views

Multiplicative error in survey data

I'm working on a panel survey data where each individual's income was multiplied by a individual-specific random number (each random number is evenly distributed from 0.5 to 1.5) to avoid any ...
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0answers
12 views

Error message using plm in R: Variable length differ [migrated]

I have a problem using the plm-package in R: assuming that data1 is my dataset, I treid to estimate pooled OLS model: ...
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1answer
114 views

When is a proper scoring rule a better estimate of generalization in a classification setting?

A typical approach to solving a classification problem is to identify a class of candidate models, and then perform model selection using some procedure like cross validation. Typically one selects ...
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14 views

How to determine error bars given number of flips [duplicate]

I have a biased coin; it's going to return either heads or tails at some percentage. If I run a test and get back say 28 heads out of 40 flips, how can i best add error bars to indicate i don't have ...
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1answer
32 views

How to measure Accuracy

I want to measure the accuracy of my GPS Receiver module. The real coordinates are obtained from the Google Maps, and the actual received coordinates are the ones that the GPS receiver received. I ...
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28 views

Optimism bias - estimates of prediction error

The book Elements of Statistical Learning (available in PDF online) discusses the optimisim bias (7.21, page 229). It states that the optimism bias is the difference between the training error and the ...
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0answers
39 views

Abnormally high accuracy with repeated 10-fold CV and ordinal regression

I am using repeated 10-fold CV to calculate the accuracy of my ordinal regression model. I have 6 predictors, 10 ordered response categories, and a total of 1166 data points. For the ordinal model, ...
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0answers
27 views

Single ARMA model for multiple time series

I have 365 days of hourly data (24points each) of a prediction error (realised -pred_day_before). I want to model the evolution of the prediction error as an ARMA process. Matlab System ...
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2answers
95 views

Does the slope of a regression between observed and predicted values always equal the $R^2$ of the original model?

As the title to my question says, I am confused as to when the $R^2$ of a model fit does not equal the slope of the regression between observed and predicted values. I am trying to present model ...
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1answer
41 views

Testing whether error variances of two regression models are equal

Is it possible to test the following? Assume you have two linear regression models, one regressing $Y_1$ on $X_1$ the other $Y_2$ on $X_2$. This gives error variance $\sigma_1^2$ and $\sigma_2^2$. ...
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0answers
31 views

What does the term “Estimation error” mean?

I was reading some notes on machine learning when I came across the following sentence: First, we may have a large estimation error. This means that, even if the true relationship between x and ...
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0answers
29 views

How to measure the period of an oscillation with least error?

I have a question about analyzing the data from a coupled pendulum. I have measured the amplitude $\psi(t)$ which is expected to be a beat and I want to measure the period. The ideal plot would be ...
2
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1answer
44 views

Chi-squared & Pearson correlation coefficient

I have just ended my math's assignment and my chi-squared test approved the null hypothesis that my data are independent; however, pearson's correlation coefficient is -0.23. Can they therefore be ...
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1answer
91 views

Why do we say that the variance of the error terms is constant?

I always think about the error term in a linear regression model as a random variable, with some distribution and a variance. So if the error terms come from this random variable, why do we say that ...
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32 views

Uncertainty in gradient of data

So I have a set of 9 x,y values, and I need to find the gradient/slope of the data, AND its associated error. Without the error, I would've used Excels LINEST function, but as the errors in my y ...
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1answer
65 views

How to calculate relative error when the true value is zero?

How do I calculate relative error when the true value is zero? Say I have $x_{true} = 0$ and $x_{test}$. If I define relative error as: $\text{relative error} = \frac{x_{true}-x_{test}}{x_{true}}$ ...
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0answers
48 views

Scale independent forecast error metric that works with changing signs

I am trying to analyze a quite large (~25,000 rows) dataset of cash flow forecasts. Receipts and expenses are aggregated, thus I may end up with the following data: ...
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2answers
67 views

What does error refer to in linear regression notation?

I regularly see linear regression models written in this notation: $y = a + \beta X + error$ I've never really pinned down what $error$ actually refers to. In the linear regression plotted below, ...
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2answers
91 views

What is the RMSE of k-Fold Cross Validation?

I am testing a neural net to predict numeric values. For that i am using a Training,Validation and Test split. I made a manual 4-Fold CV, this means i am getting 4 RMSE error, each one is the error ...
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1answer
99 views

How to simulate only stationary AR(1) with φ = 0.9?

I am interesting in simulating AR(1) processes with 0.9 parameter and n = 10. The itterations should be 10000. When I was trying to run the program it gave me an error in the estimation procedure. ...
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30 views

Error Propagation vs Standard Deviation

Say you have a set of data of lengths, widths, and heights of a rectangular box. Why do we have to use error propagation to calculate the std. dev. of the box's volume? Why couldn't we calculate the ...
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1answer
47 views

Confidence interval and margin of error

Lets say I have confidence interval at 85% with 4% margin of error, and I get a value from my analysis equal to $x$. Does this mean that if I were to perform the test 100 times, then at least 85 ...
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1answer
26 views

Error propagation on correlated Poisson samples

If I have a set of $n$ tuples ($b_1,b_2,b_3,b_4,x,y,z$), where $b_1, b_2, b_3$ and $b_4$ are counters ruled by $P_1, P_2, P_3$ and $P_4$ Poisson distributions (error on the counters are $\sqrt{b_1}$, ...
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1answer
45 views

Measurement error in maximum counts

I'm familiar with the concept of a mean value of data and the variation around the mean. Is it possible to quantify variation around maximum values? For example, take the below data collected across ...
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31 views

Running Mantel test in ape with missing values

I am running a Mantel test using the mantel.test in ape package. In the beginning, I've created distance matrices; dist.mat <- function(distances, dimension) { ...
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17 views

How to report multiple experimental observations each with their own error.

Hi I have experimental observations that look like this. The output is not a function of concentration, so I thought within each experiment they could just be considered repeated observations. ...
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3answers
195 views

Is there an overfitting in the data?

In my training set, I have 4026 instances, two classes and 104 attributes. The training error (error on the entire training set) is about 14% and 10 fold CV error on the training set is about 27%. ...
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1answer
47 views

Calculating some kind of confidence or error rate for a set of binary data

Newbie question here. I'm calculating error rates from software test results. Basically for any particular test run it's going to pass or fail, in this case, because of inherent race conditions in the ...
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0answers
17 views

Comparing sample distributions. What should I normalize by for lower population sample distributions?

I'm sorry if I'm not describing this accurately. I have a distribution of lengths of a protein. For proteins that are near the average length, I have many more data points, considering there are ...
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3answers
142 views

Fitting data to a Poisson distribution, what are the errors?

I have large data set of $\approx 10^6$ points where each point contains the information of a (year, count) of a particular event. There are many counts for a ...
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3answers
338 views

Error bars using median absolute deviation

I have tried to find a solution to my question on Google, but I can’t seem to find much information about error bars and median absolute deviation and I do not know much about statistical error ...
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1answer
164 views

Minimizing relative error (or mean square error) and maximizing likelihood

I'm not a statistician, so I would appreciate an answer in the simplest possible words. I've read that, in some sense, when we minimize the mean square error, we are maximizing the likelihood. This ...
1
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1answer
46 views

How to Reduce Error Term

My question is "What could you do if you wanted to reduce the error term (e)? I know the error term is basically the distance between the line and the point but I don't know how you would reduce it. ...
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0answers
14 views

Test/score or measure for predicted versus actual long-run proportions/averages?

What I am doing is that I have categories A, B, C, D, E. I am computing predicted long-run proportions of falling into each category and computing actual long run proportions of falling into each ...
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0answers
12 views

Appropriate accuracy test if drawing distributions on a set of actual values and predicted values?

My question regards statistics as applied to text mining. I have used substring matching to determine the predicted set of keywords. I then classify those keywords into broader groups. Given a ...
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23 views

How to combine two fitted variables

I have fitted two (and probably more) sets of data to a model using least-squares regression. So I've got the parameter values together with their errors and a reduced chi-squared for both. The data ...
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0answers
36 views

Is there a systematic study of the effects of choosing the wrong distribution to model data?

I would like to know if there is any study showing what are the effects of modelling data using the wrong probability distribution. Any reference to papers or books explaining it (possibly for a ...
2
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1answer
67 views

Comparison of two error distributions to determine “goodness of fit”

I am a physicist who is a few years out of doing his last course in statistics, so I am hoping to get some advice when comparing some data I recently generated. The context is as follows. I have two ...
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1answer
64 views

How to compare two models' MSE if the answer range differs?

I have two prediction models. The first one returns answers in the range 0 to 1, where the correct answer is 0 or 1. The second returns answers in the range -1 to 1, and the correct answer is -1 or 1. ...
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1answer
50 views

How to calculate relative error?

Let's say I have a sensor that measures pressure in a range from 10 - 60 mmHg. This sensor has an error of +/- 0.8 mmHg. Is there a way to quantify how large this error is with respect to the range ...
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1answer
61 views

The logic behind MSE

Why is it customary to use mean square error rather than mean absolute error (absolute value of target - output)? Specifically in neural networks - does it have anything to do with its convenient ...