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� Estimation error
, 2007
"... statistical model: X = h(t; q) + ɛ � h: mathematical model such as ODE model, PDE model, algebraic model, etc. � ɛ: random variable with some probability distribution such as normal distribution. � X is a random variable. Under the assumption of ɛ being i.i.d N(0, σ2), we have probability distributi ..."
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statistical model: X = h(t; q) + ɛ � h: mathematical model such as ODE model, PDE model, algebraic model, etc. � ɛ: random variable with some probability distribution such as normal distribution. � X is a random variable. Under the assumption of ɛ being i.i.d N(0, σ2), we have probability distribution model: g(xθ) = 1 √ exp
Estimation Error of Expected Shortfall
"... The problem of estimation error of Expected Shortfall is analyzed, with a view of its introduction as a global regulatory risk measure. I. ..."
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The problem of estimation error of Expected Shortfall is analyzed, with a view of its introduction as a global regulatory risk measure. I.
Estimating standard errors in finance panel data sets: comparing approaches.
 Review of Financial Studies
, 2009
"... Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solut ..."
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Cited by 890 (7 self)
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solutions to this problem. Corporate finance has relied on clustered standard errors, while asset pricing has used the FamaMacBeth procedure to estimate standard errors. This paper examines the different methods used in the literature and explains when the different methods yield the same (and correct
DISTANCE ESTIMATION ERROR IN
"... The purpose of this study was to determine the accuracy of the typical adult’s ability to view, then estimate, distances along a roadway. A survey was conducted along a roadway, where 123 subjects were asked to look at, and then estimate the distance to common objects along the roadway. The entire p ..."
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population tended to underestimate distances to objects that were from 20 to 400 feet away. After none outliers were identified and removed, the average estimation error was –23.4%. The variation in performance among individuals was extremely large, with error extremes ranging from –96 % to +71
THE EFFECTS OF ESTIMATION ERROR
, 2001
"... This paper uses Monte Carlo simulations to assess the impact of noisy input parameters on the accuracy of estimated portfolio credit risk. Assumptions about input quality are derived from the distribution of historical sample statistics commonly used in default risk modelling. The resulting estimati ..."
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estimation error in the distribution of portfolio losses is considerable. Losses that are judged to occur with a probability of 0.3 % may actually occur with a probability of 1%. The paper also shows that estimation error leads to biases in VaR estimates and significance levels of backtests. The biases can
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
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Cited by 726 (8 self)
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thatlike the other methodsthe errorcorrecting code technique can provide reliable class probability estimates. Taken together, these results demonstrate that errorcorrecting output codes provide a generalpurpose method for improving the performance of inductive learning programs on multiclass
ModelBased Analysis of Oligonucleotide Arrays: Model Validation, Design Issues and Standard Error Application
, 2001
"... Background: A modelbased analysis of oligonucleotide expression arrays we developed previously uses a probesensitivity index to capture the response characteristic of a specific probe pair and calculates modelbased expression indexes (MBEI). MBEI has standard error attached to it as a measure of ..."
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Cited by 775 (28 self)
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reduces the variability of low expression estimates, and provides a natural method of calculating expression values for PMonly arrays. The standard errors attached to expression values can be used to assess the reliability of downstream analysis. Published: X Month 2001 Genome Biology...
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