Oscillator fluctuations are described as the phase or frequency noise spectrum, or in terms of a wavelet variance as a function of the measurement time. The spectrum is generally approximated by the `power law,' i.e., a Laurent polynomial with integer exponents of the frequency. This article extends the domain of application of PVAR, a wavelet variance which uses the linear regression on phase data to estimate the frequency, and called `parabolic' because such regression is equivalent to a parabolic-shaped weight function applied to frequency fluctuations. In turn, PVAR is relevant in that it improves on the widely-used Modified Allan variance (MVAR) enabling the detection of the same noise processes at the same confidence level in a shorter measurement time. More specifically, we provide (i) the analytical expression of the response of the PVAR to the frequency-noise spectrum in the general case of non-integer exponents of the frequency, and (ii) a useful approximate expression of the statistical uncertainty.

翻译：振动器波动被描述为阶段或频率噪声频谱,或按测量时间的函数波盘变化,该频谱一般被“功率法”,即劳伦多式波段,与频率的整数引言相近。这一条扩展了PVAR的应用范围,即波段波动,利用阶段数据的线性回归来估计频率,称为“抛物线”,因为这种回归相当于对频率波动应用的抛物线形重量函数。反过来,PVAR具有相关性,因为它改进了广泛使用的变形阿伦差异(MVAR),以便能够在较短的测量时间内在同一信任水平上检测相同的噪声过程。更具体地说,我们提供了(一) PVAR对频率非内位标的频率波段的反应的分析表达,以及(二) 有用的统计不确定性的大致表达。