This article reviews the Bayesian inference with the Monte Carlo Markov Chain (MCMC) and the Hamiltonian Monte Carlo (HMC) samplers as a competitor of the classical likelihood statistical inference ...for pharmacometricians. The MCMC and the HMC samplers have greatly contributed to realization of the Bayesian methods with minimal requirement of mathematical theory. They do not require any closed form of the posterior density nor linear approximation of complex nonlinear models in high dimension even with non-conjugate priors. The HMC even weakens the dependency of the chain and improves computational efficiency. Pharmacometrics is one of great beneficiaries since they use complex multivariate multilevel nonlinear mixed effects models based on the restricted maximum likelihood estimation. Comprehension of the Bayesian approach will help pharmacometricians to access the data analysis more conveniently.
We examined the effects of oil prices along with fundamental economic variables on exchange rate movements in the Korean and Japanese foreign exchange markets, using two-regime Markov Regime ...Switching Models (MRSMs) over the period from January 1991 to March 2019. We selected the best MRSMs explaining their exchange rate movements using the Maximum Log-Likelihood and Akaike Information Criteria, and analyze effects of oil prices on their exchange rates based on the selected best MRSMs. We consider two regimes, regime 1 with high-volatility and regime 2 with low-volatility. In Korea, two apparent regimes are observed, and unstable regime 1 consists of two distinct prolonged periods, the 1997 Asian Financial Crisis and the 2008 Global Financial Crisis. Meanwhile in Japan, no evident prolonged regimes are observed. Rather, the two regimes occasionally alternate. Oil prices influence exchange rate movements in regime 2 with low-volatility in Korea, while they do not influence exchange rate movements in either regimes in Japan. The Japanese foreign exchange market is more resistant to external oil price shocks because the Japanese industry and economy has less dependence on oil than Korea.
Designing products to satisfy customers’ emotion requires the information gathered through the human senses, which are visual, auditory, olfactory, gustatory, or tactile senses. By controlling ...certain design factors, customers’ emotion can be evaluated, designed, and satisfied. In this study, a systematic approach is proposed to study the tactile sense regarding the surface roughness. Numerous pairs of antonymous tactile adjectives are collected and clustered. The optimal number of adjective clusters is estimated based on the several criterion functions. The representative average preferences of the final clusters are obtained as the estimates of engineering parameters to control the surface roughness of the commercial polymer-based products.
The usefulness of pharmacokinetics of bortezomib for multiple myeloma (MM) with respect to the maximum response to bortezomib and bortezomib-induced peripheral neuropathy (BIPN) development was ...studied. Maximum response to subcutaneous bortezomib therapy and BIPN occurrence for the first 12 weeks of treatment in 35 MM patients treated by bortezomib–dexamethasone (VD) and bortezomib–melphalan–prednisone (VMP) were evaluated. On day 1 of cycle 1, seven whole-blood samples were collected for 3 h after dosing completion to obtain the maximum plasma concentration and area under the time–concentration curve during 3 h postdose (AUC0–3) in each patient. A total of 35 patients with complete data were analyzed and the overall response rate was 91.4%. Complete response (CR) was observed in 42.9% patients. The maximum plasma concentration (Cmax) was significant for the CR rate in two different models full modelodds ratio (OR)=1.092; P=0.038, final modelOR=1.081; P=0.038. In addition, Cmax was associated with a progression-free survival advantage. Overall, 48.6% of patients developed BIPN including peripheral sensory neuropathy and neuralgia. The VMP-treated patients had a higher risk compared with the VD-treated patients (OR=21.662; P=0.029). Cmax had a tendency to affect the occurrence of BIPN (≥grade 2) (OR=1.064; P=0.092). In real-world clinical practice using bortezomib for MM patients, Cmax among pharmacokinetic factors significantly affected the achievement of CR. The VMP-treated patients showed vulnerability to BIPN, suggesting the necessity for more careful monitoring.
Named data networking (NDN) is a novel communication paradigm that employs names rather than references to the location of the content. It exploits in-network caching among different nodes in a ...network to provide the fast delivery of content. Thus, it reduces the backhaul traffic on the original producer and also eliminates the need for a stable connection between the source (consumer) and destination (producer). However, a bottleneck or congestion may still occur in very crowded areas, such as shopping malls, concerts, or stadiums, where thousands of users are requesting information from a device that resides at the edge of the network. This paper provides an analysis of content delivery in terms of the interest satisfaction rate (ISR) in ultra-dense network traffic situations and presents a final and an adequate statistical model based on multiple linear regression (MLR) to enhance ISR. A four-way factorial design was used to generate the dataset by performing simulations in ndnSIM. The results show that there is no significant interaction between four predictors: number of nodes (NN), number of interests (NI) per second, router bandwidth (RB), and router delay (RD). Moreover, the NI has a negative effect, and log(RB) has a positive effect on the ISR. The NN less than 10 has a significantly higher effect on the ISR compared with other nodes’ densities.
•The bias caused by early information loss in the time-to-event modeling has never been reported.•Using the PIEM-algorithm, the biased modeling results (Kaplan-Meier plot) caused by early information ...loss were corrected.•This method may help researchers obtain unbiased time-to-event models when the early information loss is severe.
Typical clinical data can suffer routine information loss when event times are rounded to the nearest day and right-censored at the end of follow-up. Because of the daily basis recording system, for the first 24 h, there are no events, which can damage the estimation of the Weibull survival model. Its estimation bias is inevitable since, for this short period, massive events might have occurred, the data is missing, and the fitted Weibull model is to show a steep slope. This phenomenon of estimation bias caused by the information loss caused by the problem of measurement resolution has not been properly discussed so far.
We propose a partial imputation Expectation Maximization (PIEM)-algorithm to estimate missing lifetimes only for day 1 at the mode among the whole clinical follow-up days. Based on various Weibull distributions, we simulated clinical sets after rounding and censoring raw event times and prepared chimera sets by partially substituting the imputed lifetimes only for the 24 h at the mode among the entire clinical sets.
For shape parameter ≤ 1, almost all the 95% prediction intervals (PIs) of both parameters in the chimera sets include their true values, while those in the clinical sets miss most of the true shape parameters and some of the true scale parameters. Estimating a small proportion of missing data only for the 24 h period, while keeping the rest as they are, greatly reduces biases of both scale and shape parameters. For shape parameter >1, the chimera sets consistently outperform the clinical sets.
The PIEM-algorithm may be applied as an intuitive tool for time-to-event modeling of survival data with this kind of information loss.
Korea imports all of its crude oil, and is the world's fifth largest oil importing country. We analyze the effects of oil prices, interest rates, consumer price indexes (CPIs), and industrial ...production indexes (IPIs) on the regime shift behavior of the Korean exchange rates against the USA from January 1991 to March 2019. We use the Markov regime switching model (MRSM) to detect the regime shift behavior of the movements of Korean exchange rates. In order to select the optimal MRSM, we fit a total of 30 models considering four explanatory variables. The selected model based on Akaike information criteria (AIC) and maximum log likelihood (MLL) includes the log-differentials of oil prices, the log-differentials of CPIs compared to those of the US, and its own auto-regressive terms. Based on the selected MRSM model, throughout all markets, we find evidence to support the existence of two distinct regimes: a stable regime with low-volatility, and an unstable regime with high-volatility. The regime with high-volatility includes the Asian financial crisis of 1997 and the global financial crisis of 2008–2009 in the Korean exchange rates market. In the regime with low-volatility, the Korean exchange rates are not significantly influenced by any of the explanatory variables, except for its own auto-regressive terms. In the regime with high-volatility, the Korean exchange rates are significantly influenced by the CPIs and oil prices. The transition probability from the regime with low-volatility to the regime with high-volatility is about ten times that of the opposite case.
Since the Asian financial crisis and the global financial crisis, the regime shift behavior has been notable in the stock markets. We examine the effects of interest rates and foreign exchange rates ...on stock returns and the cross-correlations of Korean stock returns associated with three other countries: Japan, USA, and China, using the Hamilton 2-regime Markov Switching model, for the period January 1993–December 2016. In both regimes, the volatility in the Korean stock market is greater than Japan and USA, but less than China. In regime 1 with low-volatility, the stock returns of both Korea and Japan are significantly affected first by their exchange rates and then by their interest rates. In regime 2 with high-volatility, the Korean stock market is explained by neither of the two exogenous variables while the Japanese stock returns respond positively to the exchange rates but negatively to the interest rates. The transition probability from regime 1 to regime 2 is greater than the reverse probability in the Korean stock market, which is opposite in Japan. Considering all four countries simultaneously, the Korean stock market is highly influenced by both the US and Japanese stock market in regime 1 with low-volatility, but only influenced by the Japanese stock market in regime 2 with high-volatility.
The authors consider multivariate analysis of variance procedures based on the multivariate spatial ranks. Two models are considered: the location-family model and the fully nonparametric model. ...Procedures for testing main and interaction effects are given for the 2 × 2 layout.
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