• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.230-235
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• 1999

In this paper, Using third-order system of the PLL we analyze the aspect of flicker noise appearing troubles In the low frequency band. Since i. Is difficult to analyze mathematically flirter noise In the third-order system of the PLL, introducing the concept of pseudo-damping factor using the optimized second-filter makes an ease of the access of the flicker-noise variance. we'll show a numerical formula of flicker variance in the third-order system of the PLL which is compared with that of 1/f-noise variance in the second-order system of the PLL.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.135-141
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• 2006

Cusum control chart is used for the purpose of controling the process mean. We consider the problem related to cusum chart for controling process variance. Previous researches have considered the same problem. The main difficulty shown in the related researches was to derive the ARL function which characterizes the properties of the chart. Sample variance, differently with sample mean, follows chi-squared type distribution, even when the quality characteristics are assumed to be normally distributed. The ARL function of cusum is described by a type of integral equation. Since the solution of the integral equation for non-normal distribution is not known well, people used simulation method instead of solving the integral equation directly, or approximation method by taking logarithm of the sample variance. Recently a new method to solve the integral equation for Erlang distribution was published. Here we consider the steps to apply the solution to the problem of controling process variance.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.6
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• pp.121-127
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• 1997

Multilayer feedforward networks may be applied to identify the deterministic relationship between input and output data. When the results from the network require a high level of assurance, consideration of the stochastic relationship between the input and output data may be very important. Variance is one of the effective parameters to deal with the stochastic relationship. This paper presents a new algroithm for a multilayer feedforward network to learn the variance of dispersed data without preliminary calculation of variance. In this paper, the network with this learning algorithm is named as a variance learning neural network(VALEAN). Computer simulation examples are utilized for the demonstration and the evaluation of VALEAN.

• Journal of Environmental Health Sciences
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• v.18 no.2
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• pp.67-74
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• 1992

The lab-scale biological A$_{2}$O system was applied from treating piggery wastewater highly polluted organic material which nitrogen and phosphorous are much contained relatively in conversion with other wastewater. The objective of this study was to investigate the effect of variance parameters on the treatability of this system according to operation conditions. An obtained experimental data were analysed by using principal component analysis (PCA) method. The results are summarized as follows: 1. From Varimax rotated factor loading in raw wastewater, variance of factor 1 was 36.8% and cumulative percentage of variance from factor 1 to factor 4 was 81.5% and of these was related to BOD, TKN and BOD loading. 2. In anaerobic process, variance of factor 1 was 33.5% and cumulative percentage of variance from factor I to factor 4 was 81.8% and of these was related to PO$_{4}$-P, BOD, DO and Temperature. 3. In anoxic process, variance of factor 1 was 30.1% and cumulative percentage of variance from factor i to factor 4 was 84.3% and of these was related to pH, DO, TKN and temperature. 4. In aerobic process, variance of factor 1 was 43.8% and cumulative percentage of variance from factor 1 to factor 4 was 81.5% and of these was highly related to DO, PO$_{4}$-P and BOD. 5. It was better to be operated below 0.30 kg/kg$\cdot$day F/M ratio to keep over 90% of BOD and SS, 80% of TKN, and 60% of PO$_{4}$-P in treatment efficiencies. 6. Treatment efficiencies was over 93% of BOD and SS, 81% of TKN and 60% of PO$_{4}$-P at over 20$^{\circ}$C, respectively.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.55-66
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• 2012

Option pricing models using L$\acute{e}$evy processes are suggested as an alternative to the Black-Scholes model since empirical studies showed that the Black-Sholes model could not reflect the movement of underlying assets. In this paper, we investigate whether the Variance Gamma model can reflect the movement of underlying assets in the Korean stock market better than the Black-Scholes model. For this purpose, we estimate parameters and perform likelihood ratio tests using KOSPI 200 data based on the density for the log return and the option pricing formula proposed in Madan et al. (1998). We also calculate some statistics to compare the models and examine if the volatility smile is corrected through regression analysis. The results show that the option price estimated under the Variance Gamma process is closer to the market price than the Black-Scholes price; however, the Variance Gamma model still cannot solve the volatility smile phenomenon.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.177-182
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• 2008

There are times when we need more sample to achieve a more accurate estimator. Since these two sets of sample have the information about the same population, it is necessary to treat both as a single combined data. In this paper we present the unpooled sample variance for the combined data when we just know a sample mean and variance for the each data set without the raw data. It is shown that the pooled variance $s^2_p$ is always greater than the exact variance $s^2_t$ when ${\bar{x}}_n\;=\;{\bar{y}}_m$. And the difference of means for two data, ${\bar{x}}_n-{\bar{y}}_m}$, is larger, the difference of $s^2_p$ and $s^2_t$ is larger.

• Journal of the Korean Mathematical Society
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• v.57 no.5
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• pp.1167-1186
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• 2020

This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization. Our modeling framework consists of the equity which follows the dynamics of the Heston stochastic volatility model, and the stochastic interest rate is driven by the Cox-Ingersoll-Ross (CIR) process with full correlation structure imposed among the state variables. This full correlation structure possesses the limitation to have fully analytical pricing formula for hybrid models of variance swaps, due to the non-affinity property embedded in the model itself. We address this issue by obtaining an efficient semi-closed form pricing formula of variance swaps for an approximation of the hybrid model via the derivation of characteristic functions. Subsequently, we implement numerical experiments to evaluate the accuracy of our pricing formula. Our findings confirm that the impact of the correlation between the underlying and the interest rate is significant for pricing discretely-sampled variance swaps.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.154-156
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• 2017

Constant variance of degradation data over time has been generally assumed to estimate storage lifetime using destructive, accelerated degradation data over time. However, performance data of ammunitions deteriorate over time, and the standard deviation would tend to increase over time. This paper shows storage lifetime comparison results for constant variance and time-variant variance assumptions of degradation data over time, and proposes that time-variant variance assumption should be considered to increase accuracy in lifetime estimation.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.981-999
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• 2017

In the standard control chart assuming a simple random model, we estimate the process variance without considering the between-sample variance. If the between-sample exists in the process, the process variance is under-estimated. When the process variance is under-estimated, the narrower control limits result in the excessive false alarm rate although the sensitivity of the control chart is improved. In this paper, using the variance component model to incorporate the between-sample variance, we set the control limits using both the within- and between-sample variances, and evaluate the efficiency of the control chart in terms of the average run length (ARL). Considering the most widely used control chart types such as ${\bar{X}}$, EWMA and CUSUM control charts, we compared the differences between two cases, Case I and Case II, where the between-sample variance is ignored and considered, respectively. We also considered the two cases when the process parameters are given and estimated. The results showed that the false alarm rate of Case I increased sharply as the between-sample variance increases, while that of Case II remains the same regardless of the size of the between-sample variance, as expected.

• Korean Journal of Hydrosciences
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• v.6
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• pp.13-22
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• 1995

The augmenting hydrologic data using a correlation procedure has been used to improve the estimates of the mean and variance at the site of interest with short record when one or more near by sites with longer records are available. The variance of the unbiased maximum likelihood estimator of $ derived by Moran based on the multivariate normal distribytion is modified into the form of Matalas and Jacobs for the biveriate normal distribution to get the critical minimum values of the multiple correlation coefficient which give the improvement for estimating the variance at the site of interest. Those values are tabulated for various lengths of short records and the number of sites.