The error of an estimate or prediction is its deviation from the true value, which may be unobservable (e.g., regression parameters), or observable (e.g., future realizations). Use the [error-message] tag to ask about software errors.

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How do I know if LHS will reduce my sampling error?

In this paper: http://salserver.org.aalto.fi/vanhat_sivut/Opinnot/Mat-2.4108/pdf-files/emat08.pdf equation 6 shows that if $cov(f(x_1),f(x_2))$ is positive LHS does not reduce random sampling error. ...
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8 views

Goodness of fit when all your variables have errors?

I have $N$ measurements of type $(X_i,Y_i,Z_i)$ where each measurement has uncertainty $({\sigma_X}_i,{\sigma_Y}_i,{\sigma_Z}_i)$. I am trying to fit these measurements to a plane: $Z = \alpha X + \...
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got msg “convergence warning in initialization\n” running svmpath() [on hold]

I got msg "convergence warning in initialization\n" running svmpath(). Data consist of 15 factors, transformed by "model.matrix" into 84 constrasts; 4452 instances. ...
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1answer
11 views

datav alidation on lexcel [on hold]

I have given data validation for Std. warehouse as "YGCTCAP1" and "YGCTBAP1" for the first row i entered YGCTCAP1 by drop down, and i drag down the cell, it in became YGCTCAP2, --3,--4 ETC , ...
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10 views

What an error rate in regression means ? [closed]

As I cannot say that the error in regression means precision as in classification. What an error rate after the system has been cross-validate in regression means ?
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11 views

Accuracy of sampling from a Gaussian distribution

I am currently sampling data points out of a Gaussian distribution with a particular mean and standard deviation. I want to compare how close the sampled Gaussian distribution is to the Gaussian ...
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12 views

Making use of SEs of parameter estimates when making group comparisons

I have a bunch of behavioural data and collapsed every individual participant's responses into a single parameter (threshold of a psychometric function but that's not really important) for which I ...
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21 views

Realistic measurement errors on simulated observations

I have a code that simulates stars in a galaxy, outputting positions and velocities. I plug this data into another code to do some further analysis. Normally you'd also put in instrumental errors of ...
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5 views

Comparing two CDF with normalized Kolmogorov-Smirnov

The Kolmogorov-Smirnov (KS) test is a well-known metric if you want to compare two CDF. It computes the maximum difference between the two. The main concern I have ...
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17 views

Consequences of violating assumptions about errors in IRT/Rasch based models

In the sorts of measurement models to which one might apply IRT models, including Rasch models, there is not thought to be an error associated with the latent variable. Rather, the latent variable is ...
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15 views

Arithmetic vs Geometric mean for absolute error of a rate [duplicate]

What is the most appropriate average to use if I want to compute the average of the absolute error of a rate? Example: This sounds a bit complicated, so let me break it down. Suppose I have a box ...
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28 views

Line of best fit for data with error in x and y

I have a two dimensional dataset which comes from prior statistical analysis. Each point $(x_n,y_n)$ in the dataset has an error estimate $\sigma_{x,n}, \sigma_{y,n}$ for both coordinates. The $x_n$ ...
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2answers
115 views

RMSE - where this evaluation metric came from?

Does anyone know where this metric came from ? Can someone bring article references or something like this? Im actually wondering if there's any mathematical concept or any way to demonstrate ...
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1answer
6 views

Determining confidence for individuals' performance

Apologies if this is ridiculously basic - I have searched the site but my vocabulary is probably too limited to be successful. I have a group of individuals performing a task with a boolean outcome - ...
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28 views

Which is the dimension (or units) of the predicted random effects?

Consider a simple panel data (or multilevel model) with random effects. Say the dependent variable $y_{ij}$ is measured in output per year. The regression to be estimated is: $$y_{ij}= X_{ij}\beta + \...
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13 views

Uncertainty on the standard deviation of data set, when the data points are uncertain

I have a set of four data points (x,y), and I would like to describe the spread of the data about the mean in both the x-direction and in the y-direction. Each individual data point has an uncertainty ...
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1answer
131 views

Logistic regression - correcting for differing quality of observations

I'm stuck with the following problem. I want to run a predictive logistic regression. My dependent variable is binary (0,1). My predictor is a continuous variable. However, the quality of ...
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1answer
36 views

Estimating the variation of the scaling factor from a transformation onto a theoretical graph

I have a numerically calculated graph, on unit-less coordinates. I have experimental data which corresponds to a point on that graph. The data has units, and to make it unitless one has to divide it ...
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20 views

Variance of error $Y^* = y_i/c_i$

If I have this model: $Y_i = B_1 + B_2\log x_i + 2e_i$ $e_i\sim N(0, σ^2)$, how to solve this $Y^* = y_i/c_i$ --------> if : $V(Y^*) = \sigma^2$ ? The constant is $c_i = 1/2$?
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1answer
41 views

SVM training and testing error interpretation

I am new to machine learning and I just used SVM for the first time to analyze my dataset... Now I have created a figure that displays the training and testing error of the model as a function of ...
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1answer
81 views

What is the proper way to measure error for an estimation algorithm?

Our algorithm is about estimating the true statistic values from a data set. The data set is a table in relational database, we are going to estimate the statistic value for filtered records, like <...
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22 views

How can I decompose the error after an ARIMA estimation, and how do I store the estimated values?

EDIT (in response to Stephan's comments): I was able to read a paper by Bessembinder & Seguin (1992) on futures trading and stock price volatility, wherein they used the ARIMA model to decompose ...
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16 views

Find error on the inputs

Suppose that we have a model with an input and an output. The model is exact (no structural uncertainty). However there is an error in the output ( the error is detected from already given exact ...
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12 views

Estimation of the linear regression with non-conventional error distribution

I am trying to estimate the regression model, say standard linear model, with the error term having a Pareto distribution instead of normal. Although it is fairly straightforward to construct the ...
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1answer
31 views

Cross Validation Train Test Gap Question

Question: is minimizing test set mean validation error more important than the gap between train and test errors? Let's say I can tweak parameters in my model to give me mean validation error of 4500 ...
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1answer
16 views

Loss function/error measurement for allocation problem

I'm working on a prediction rule for an allocation problem. So, it's data like this: ...
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28 views

Does the unconditional distribution of $y_i$ only depend on the distribution of the errors?

In linear regression, does the unconditional distribution of $y_i$ only depend on the distribution of the errors? For example, is it not the case that if $$y_i = \beta_0 +\beta_1 x_i + u_i $$ and ...
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19 views

Tweaking SVM error rates?

I currently have a one-vs-all SVM setup. Each SVM outputs a score. If I take the maximum score as the correct corresponding class, this gives me FARs of 0.008%. However it also gives me FRRs of about ...
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1answer
45 views

Is the margin of error for a survey a “fake” statistic?

When I conduct a survey for a client, they are often very concerned about the margin of error for the survey, and that’s totally reasonable. Oftentimes however, when they say, “We want a margin of ...
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9 views

An appropriate measure of predictive accuracy on non-uniform data?

When you have a model making a prediction about non-uniform data, how do you approach deciding on an appropriate measure of accuracy? For example, if the the data tends to be a normal distribution ...
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1answer
15 views

Measuring forecasting risk of linear regression

I want to measure how much risk I take by forecasting something. I know I can measure the error and things like MAD, MSE, ...
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1answer
24 views

Other types of mean error

Let $\tilde f$ be an approximation of the function $f(x) = \arccos(x)$. I'm using MATLAB to figure out how good this approximation is by calculating a mean error. My first idea was to use this formula ...
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23 views

Why is the standard deviation the error on the singular measurement?

I'm a beginner with the study in data analysis in Physics. I'm trying to understand the meaning, in the field of experimental Physics, of the standard deviation $\sigma$ of a series of data. There ...
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31 views

Alternatives to predictions' MSE that are 'proportional' to $Y$

Assume that all values are real. let $Y$ be a vector of observations and $\hat{Y}$ be a vector of predictions. Then the MSE of the predictions is $$1/n\sum_{i=1}^n(\hat{Y}_i-Y_i)^2$$ Let $$S = \{s~...
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11 views

Planned Orthogonal Comparison Type I Error Rate and the Number of Independent Contrasts

I am confused about Type I error rate and the number of planned independent contrasts in Planned Orthogonal Comparisons in one-way ANOVA. If we have a factor with 5 groups and we would like to test ...
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22 views

Using a change detection error matrix approach for raster aggregation

I am assessing annual land use change along a 10 year period and have rasterized a vector land use dataset to base resolution 'n' metres to do so (vector data is taken as ground truth, errors in it ...
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1answer
41 views

Error term in multiple regression model

I am trying to run a multiple regression model to see the effect of field characteristics such as soil texture, slope and hydraulic conductivity on drainage density. My samples are agricultural ...
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20 views

Modeling error in regression

A few weeks ago I posted in this forum about a regression analysis I wanted to run. My outcome was number of organs and they values went from 1-7. Well, as someone pointed out, I could have some bias. ...
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31 views

Estimator of true probability — understanding margin of error for very small probability

I have a coin whose probability of landing on heads when flipped is unknown, but could be anywhere between 0 and 100%. I want to flip the coin some number of times and estimate the true probability ...
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10 views

Gini impurity and generalization error

Has anyone seen papers on relationship between information-based criterions (such as Gini impurity, information gain etc.) and generalization error? Is there theoretical justification of using such ...
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40 views

Forecast accuracy metric for forecasts over different time horizons

I a dataset of 81 oil price forecasts from more than 30 different forecasters. Those forecasts consist of a forecast made on various days in 2014 for the average oil spot price of 2015. For instance, ...
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1answer
24 views

How can I deal with numerical errors in a large-scale linear regression?

I am currently conducting a linear regression on a large-scale data set which has many sparse features ($\simeq 10^5$) and many observations ($\simeq 10^6$) by using scikit-learn. (Most of the ...
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1answer
37 views

Prediction interval, forecast error for a function of a forecast

I have two variables $X$ and $Y$. For each variable I created a forecasting model (using time series) and estimated $X_{t+1}$ and $Y_{t+1}$ and the prediction interval and the error for each. I have ...
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11 views

Error propagation taylor second-order (multivariate)

I'm trying to understand how the second-order approximation mentioned in this posting http://stats.stackexchange.com/a/13005 looks like for a mulitvariate function. I have only found the ...
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16 views

k.means relation between sum squared error and variance

I work with k-means algorithm and I don't understand the relation between sum squared error and variance. Is there a relation between these values?. I work with k=1. And the values are Sum squared ...
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1answer
23 views

calculate the internally studentized residual

it says that ...an ordinary residual divided by an estimate of its standard deviation $s(e_{i})$ As we can see from the example that mean for four residuals is 0, so $s(e_{i})=\sqrt{\frac{(-0.2-0)^2+(...
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1answer
93 views

Relationship between RMSE and RSS

I'm working on simple linear regression, and I would like to understand the relationship between RMSE and RSS (residual sum of squares). In another Stackexchange question, I found some explanations, ...
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32 views

Log transformed MAE to original value

In order to evaluate the forecast accuracy of a model I'm using a step wise cross validation to get a MAE value and use that again to calculate the MASE. As part of the model specification the data ...
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1answer
28 views

Compare RMSE between original and logged time series data

I have some time series data, both in the original form y and in logged form log(y). I should compare the models generated by applying neural networks and find the best one. How to decide which one is ...
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Interpolating data with errors (limited model knowledge)

I have data which I know follows a function $y = f(x)$ such that it is quadratic i.e. $y =\alpha x^2$ for some $\alpha$ when $x\rightarrow 0$ and $y = \beta x$ for large $x$. The data itself has ...