Application of the Mixed Time-averaging Semiclassical Initial Value Representation method to Complex Molecular Spectra

The recently introduced mixed time-averaging semiclassical initial value representation molecular dynamics method for spectroscopic calculations [M. Buchholz, F. Grossmann, and M. Ceotto, J. Chem. Phys. 144, 094102 (2016)] is applied to systems with up to 61 dimensions, ruled by a condensed phase Caldeira-Leggett model potential. By calculating the ground state as well as the first few excited states of the system Morse oscillator, changes of both the harmonic frequency and the anharmonicity are determined. The method faithfully reproduces blueshift and redshift effects and the importance of the counter term, as previously suggested by other methods. Differently from previous methods, the present semiclassical method does not take advantage of the specific form of the potential and it can represent a practical tool that opens the route to direct ab initio semiclassical simulation of condensed phase systems.Comment: 11 figure

Application of the Inverse Almost Ideal Demand System to Welfare Analysis

This paper presents the theoretical properties of the Inverse Almost Ideal De-mand System and applies the system on time series data for cod, herring and plaice in Denmark (1986 to 2001). Furthermore, the shortcoming of the Inverse Almost Ideal Demand System when applied to welfare analysis is discussed. The properties of the demand system show that - since the demand system is a second-order approximation to the true system - it does not have global appli-cability for welfare measurement. It may, therefore, not satisfy the conditions for calculation of consumer surplus (negative slope and positive point of inter-section with the price-axis). The theoretical point is illustrated by an empirical example of the Danish fish market. Using a vector auto regressive model in er-ror correction form to overcome the problem of non-stationarity of data, the In-verse Almost Ideal Demand System is estimated. For cod the intercept is nega-tive and for herring and plaice the slope of the demand function is positive in the data interval investigated. Thus, the estimated demand system is not suitable for welfare analysis.Inverse Almost Ideal Demand System, Welfare analysis, Co-integration and Fish

Lullaby Land: Solo or Duett

https://digitalcommons.library.umaine.edu/mmb-vp/2051/thumbnail.jp

Prediction intervals for all of M future observations based on linear random effects models

In many pharmaceutical and biomedical applications such as assay validation, assessment of historical control data, or the detection of anti-drug antibodies, the calculation and interpretation of prediction intervals (PI) is of interest. The present study provides two novel methods for the calculation of prediction intervals based on linear random effects models and restricted maximum likelihood (REML) estimation. Unlike other REML-based PI found in the literature, both intervals reflect the uncertainty related with the estimation of the prediction variance. The first PI is based on Satterthwaite approximation. For the other PI, a bootstrap calibration approach that we will call quantile-calibration was used. Due to the calibration process this PI can be easily computed for more than one future observation and based on balanced and unbalanced data as well. In order to compare the coverage probabilities of the proposed PI with those of four intervals found in the literature, Monte Carlo simulations were run for two relatively complex random effects models and a broad range of parameter settings. The quantile-calibrated PI was implemented in the statistical software R and is available in the predint package