Trend filtering is known as the technique for detecting piecewise linear trends in univariate time series. This extended to setting of compositional data, which are multivariate data where only relative information importance. According this, we formulate problem and present a procedure how efficiently solve it. To show usefulness this method, consider number COVID-19 infections several Europea...

dopaminergic signaling is one of the regulatory pathways being investigated for its implication in glucose metabolism. the aim of this study was to determine the effect of cabergoline on biochemical and anthropometric parameters in prediabetes stage (impaired fasting glucose and impaired glucose tolerance). in this double blind, placebo-controlled, pilot study, 27 prediabetic adults were random...

Full simulations of homogeneous isotropic turbulence containing a homogeneous passive scalar were made at low Reynolds numbers and various Prandtl numbers. The results show that the spectral behavior of the two fields are quite similar; both fields decay as power-law functions of time. However. the decay exponent is quite dependent on both the Reynolds and Prandtl numbers. The decay exponent of...

The Hodrick-Prescott filter is the probably most popular tool for trend estimation in economics. Compared to other frequently used methods like the Baxter-King filter it allows to estimate the trend for the most recent periods of a time series. However, the HodrickPrescott filter suffers from an increasing excess variability at the margins of the series inducing a too flexible trend function at...

This study investigated if free T4 and TSH concentrations or thyroid function categories were associated with prevalent CHD and the severity of coronary atherosclerosis in a population undergoing coronary angiography. This was a cross-sectional study including 1799 patients who were consecutively admitted and underwent coronary angiography. We evaluated the severity of coronary atherosclerosis ...