Sentences with phrase «simple timing adjustments»

Not exact matches

A log, which can be as simple as a well - kept electronic calendar, also provides an honest view of where someone is spending his or her time and is a good way to assess if adjustments should be made.

A simple adjustment can fix that: Put your child down for a nap at the same time each day and put him to bed at the same time each night.

Other times it takes simple adjustments to position and latch, some tips for coping with challenges, some assurance that things will get easier in time.

And the best part is that I made a few simple adjustments to take this cake to the next level, which will allow it to hold you over longer, so you'll spend more time enjoy the best things summer has to offer, instead of being cooped up in the kitchen.

The latter project means making future adjustments to keep up with the changing times will be a much simpler matter.

I didn't spend much time with the MKT but it doesn't take long to get discouraged and annoyed with a vehicle when a simple radio or HVAC adjustment requires pinpoint fingertip accuracy and the patience of Mother Teresa.

As a final option for the rear wing, you can get the adjustable system from 1016 Industries, quick release pins combined with custom - made bearings allow a simple, yet strong way to perform adjustments based on what the customer wants to achieve at that time... more downforce or maximum top speed.

In summary, while hedging has generally been advantageous for equity investing over the past 11 years, evidence from simple tests provides little support for a belief that John Hussman successfully times the stock market via hedging adjustments based on his assessments of market valuation and market action.

My «single candle» is simple — it is an adjustment of expectations, which involves reasoning that when things have been horrible, after some amount of time, it is time to take risk again, before it is perfectly obvious to do so.

You're free to make that assumption and take it into account in your decisions, but we're keeping things simple by assuming that the time value of money is the same as the inflation adjustments.

Vision one is the huge screen in front of the risk manager, with advanced math and analytics, that takes in all the data, and allows the risk manager to make simple adjustments in real time to the quantitative feedback.

The original ICOADS global mean sea surface temperature is shown in figure 1 along with the simple war - time adjustment analysed in this study.

It is noted that the simple adjustment is consistent in the time derivative: the two primary components detected in the time series remain similar in period, phase (reference year) and magnitude in the first derivative (see appendix).

While the various studies have identified possible sources of bias, the lack of documentary evidence for the changes and the degree of speculation concerning the geographical extent, duration and timing of the changes makes the adjustments no less ad hoc than the simple adjustment.

Figures 8, 9 and 10 show the time series and the first and second time differentials for original ICOADS data, HadSST3 and the simple 0.4 K adjustment respectively.

You made the reasonable comment the the simple war - time adjustment was ad hoc.

General Introduction Two Main Goals Identifying Patterns in Time Series Data Systematic pattern and random noise Two general aspects of time series patterns Trend Analysis Analysis of Seasonality ARIMA (Box & Jenkins) and Autocorrelations General Introduction Two Common Processes ARIMA Methodology Identification Phase Parameter Estimation Evaluation of the Model Interrupted Time Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time SeTime Series Data Systematic pattern and random noise Two general aspects of time series patterns Trend Analysis Analysis of Seasonality ARIMA (Box & Jenkins) and Autocorrelations General Introduction Two Common Processes ARIMA Methodology Identification Phase Parameter Estimation Evaluation of the Model Interrupted Time Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time Setime series patterns Trend Analysis Analysis of Seasonality ARIMA (Box & Jenkins) and Autocorrelations General Introduction Two Common Processes ARIMA Methodology Identification Phase Parameter Estimation Evaluation of the Model Interrupted Time Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time SeTime Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time SeTime Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time SeTime Series