• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.107-117
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• 2003

We study the integration problem in which one wants to compute the approximation to the definite integral in the average case setting. We choose the composite Newton- Cotes quadratures as our algorithm and the function values at equally spaced sample points on the given interval［0, 1］as information. We compute the average case error of composite Newton-Cotes quadratures and show that it is minimal (modulo a multi-plicative constant).

• Honam Mathematical Journal
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• v.36 no.2
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• pp.291-303
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• 2014

In this paper, through a direct computation with subintervals partitioning [0, 1], we compute better a posteriori bounds for the average case error of the difference between the true value of $I(f)=\int_{0}^{1}f(x)dx$ with $f{\in}C^r$[0, 1] minus the composite trapezoidal rule and the composite trapezoidal rule minus the basic trapezoidal rule for $r{\geq}3$ by using zero mean-Gaussian.

• The KIPS Transactions:PartA
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• v.11A no.5
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• pp.401-406
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• 2004

Among many algorithms for the integration problems in which one wants to compute the approximation to the definite integral in the average case setting, we study the average case errors of numerical integration rules using interpolation. In particular, we choose the composite Newton-Cotes quadratures and the function values at equally spaced sample points on the given interval as information. We compute the average case error of composite Newton-Cotes quadratures and show that it is minimal(modulo a multiplicative constant).

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.365-372
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• 2003

We show that if ${\gamma}$ $\leq$ 2, the average error of the composite Trapezoidal rule on two consecutive intervals is proportional to h$\^$2h+3/ where h is the length of each subinterval of the interval [0, 1]. As a result, we show that the Trapezoidal rule with equally spaced points is optimal in the average case setting when ${\gamma}$ $\leq$ 2.

• Communications of the Korean Mathematical Society
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• v.13 no.4
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• pp.903-911
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• 1998

We show that if r $\leq$ 2, the average error of the Trapezoidal rule is proportional to $n^{-min{r＋l, 3}}$ where n is the number of mesh points on the interval [D, 1]. As a result, we show that the Trapezoidal rule with equally spaced points is optimal in the average case setting when r $\leq$ 2.

• Honam Mathematical Journal
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• v.30 no.3
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• pp.581-587
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• 2008

In this paper, to have a better a posteriori error bound of the average case error between the true value of I(f) and the Trapezoidal rule on subintervals using zero mean-Gaussian, we prove that a new average error between the difference of the true value of I(f) from the composite Trapezoidal rule and that of the composite Trapezoidal rule from the simple Trapezoidal rule is bounded by $c_rH^{2r+3}$ through direct computation of constants $c_r$ for r ${\leq}$ 2 under the assumption that we have subintervals (for simplicity equal length h) partitioning [0, 1].

• The KIPS Transactions:PartA
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• v.12A no.5 s.95
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• pp.391-394
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• 2005

In this paper, we study the average case error of the Trapezoidal rule using zero mean-Gaussian. Assume that we have n subintervals (for simplicity equal length) partitioning [0,1] and that each subinterval has the length h. Then, for $r{\leq}2$, we show that the average error between simple Trapezoidal rule and the composite Trapezoidal rule on two consecutive subintervals is bounded by $h^{2r+3}$ through direct computation of constants $c_r$.

• Journal of the Korean Statistical Society
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• v.13 no.2
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• pp.107-113
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• 1984

In a linear regression model the idependent variables are frequently subject to measurement errors. For this case, the problem of estimating unknown parameters has been extensively discussed in the literature while very few has been concerned with the effect of measurement errors on prediction. This paper investigates the behavior of the predicted values of the dependent variable in terms of the average mean square error of prediction (AMSEP). AMSEP may be used as a criterion for selecting an appropriate estimation method, for designing an estimation experiment, and for developing cost-effective future sampling schemes.

• Journal of the Korean Mathematical Society
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• v.33 no.2
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• pp.235-247
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• 1996

Many numerical computations in science and engineering can only be solved approximately since the available infomation is partial. For instance, for problems defined ona space of functions, information about f is typically provided by few function values, $N(f) = [f(x_1), f(x_2), \ldots, f(x_n)]$. Knwing N(f), the solution is approximated by a numerical method. The error between the true and the approximate solutions can be reduced by acquiring more information. However, this increases the cost. Hence there is a trade-off between the error and the cost.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.74-82
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• 2002

In Intensity Modulated Radiotherapy (IMRT), radiation is delivered in a multiple of Multileaf Collimator (MLC) subfields. A subfield with a small leaf-to-leaf opening is highly sensitive to a leaf-positional error. We introduce a method of identifying and rejecting IMRT plans that are highly sensitive to a systematic MLC gap error (sensitivity to possible random leaf-positional errors is not addressed here). There are two sources of a systematic MLC gap error: Centerline Mechanical Offset (CMO) and, in the case of a rounded end MLC, Radiation Field Offset (RFO). In IMRT planning system, using an incorrect value of RFO introduces a systematic error ΔRFO that results in all leaf-to-leaf gaps that are either too large or too small by (2ㆍΔRFO), whereas assuming that CMO is zero introduces systematic error ΔCMO that results in all gaps that are too large by ΔCMO = CMO. We introduce a concept of the Average Leaf Pair Opening (ALPO) that can be calculated from a dynamic MLC delivery file. We derive an analytic formula for a fractional average fluence error resulting from a systematic gap error of Δ$\chi$ and show that it is inversely proportional to ALPO; explicitly it is equal to, (equation omitted) in which $\varepsilon$ is generally of the order of 1 mm and Δx=2ㆍΔRFO+CMO. This analytic relationship is verified with independent numerical calculations.