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The Shift Invariant Discrete Wavelet Transform (SIDWT) with Inflation Time Series Application

机译:带通货膨胀时间序列的平移不变离散小波变换(SIDWT)应用

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Analysis of time series used in many areas, one of which is in the field economy. In this research using time series on inflation using Shift Invariant Discrete Wavelet Transform (SIDWT).Time series decomposition using transformation wavelet namely SIDWT with Haar filter and D4. Results of the transformation, coefficient of drag coefficient wavelet and scale that is used for modeling time series. Modeling done by using Multiscale Autoregressive (MAR). In a certain area, inflation to it is an important that he had made the standard-bearer of economic well-being of society, the factors Directors investors in selecting a kind of investment, and the determining factor for the government to formulate policy fiscal, monetary, as well as non-monetary that will be applied. Inflation can be analyzed using methods Shift Invariant Discrete Wavelet Transform (SIDWT) which had been modeled for them to use Mulitiscale Autoregressive (MAR) with the?R2 value 93.62%.
机译:分析在许多领域中使用的时间序列,其中之一是在现场经济中。本研究利用位移不变离散小波变换(SIDWT)对通货膨胀进行时间序列分解。利用变换小波对时间序列进行分解,即具有Haar滤波器和D4的SIDWT。转换结果,阻力系数小波系数和用于时间序列建模的标度。通过使用多尺度自回归(MAR)进行建模。在某个领域,通货膨胀对于他成为社会经济福祉的旗手,董事投资者选择一种投资的因素以及政府制定政策性财政的决定性因素至关重要,货币和非货币。可以使用位移不变离散小波变换(SIDWT)方法对通货膨胀进行分析,该方法已为之建模,以使用R2值为93.62%的多尺度自回归(MAR)。

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