HPLC A PRAACTICAL USER''''S GUIDE PART 6 POTX

The OUTPUT statement creates an output SAS data set as specified by the following options.OUT=SAS-data-setnames the output SAS data set containing the predicted and transformed values. If the OUT=option is not specified, the new data set is named according to the DATAn convention.ALPHACLI=numbersets t[r]

6 . . 23556.10 23556.107 . . 24953.80 24953.80Example 36.4: Limiting the Time Range of DataYou can also limit the time range of the data in the SAS data set by using the RANGE= option in theLIBNAME statement or the WHERE statement in the DATA step to process the time ID variableDATE only when[r]

forecasts affect the D10.A forecasts only indirectly through the impact of the regARIMAforecasts on the seasonal factors that are shown in Table D10.Tables that contain forecasts, standard errors, and confidence limits are displayed in associationwith the FORECAST statement. If the data is tra[r]

model y1 y2 y3 y4 = x1 x2 x3 x4 x5 </options>;model y1 y2 y3 y4 = x1-x5 </options>;model y1 = x1-x5, y2 = x1-x5, y3 y4 = x1-x5 </options>;model y1-y4 = x1-x5 </options>;When the multivariate model has different independent variables that corres[r]

2590 ✦ Chapter 37: The SASEHAVR Interface EngineIf you also want to see a list of all the variables and their corresponding labels for this data set, youcan run the CONTENTS Procedure.Output 37.12.2 shows the output.Output 37.12.2 SHORT= Option Shows the Contents of the ValidE2 Data SetAlphab[r]

2652 ✦ Chapter 39: Getting Started with Time Series ForecastingFigure 39.34 Selecting Models to FitThe system fits the two models you selected. After the models are fit, the labels of the two modelsand their goodness-of-fit statistic are added to the model table, as shown in Figure 39.35.Model List and[r]

The results of this trend analysis are shown in Output 29.2.4.1906 ✦ Chapter 29: The TIMESERIES ProcedureOutput 29.2.4 Trend StatisticsUsing the season statistics stored in the WORK.SEASON data set, the following statements plotvarious season statistics for each season.title1 "Seasonal Statistics";p[r]

The Time ID decomposition listing and plot shown in Output 28.1.1 and Output 28.1.2 summarizehow well the WEEK3 interval fits the time ID values by showing the number of counts, offsets, andspans for each time interval that is represented by the DATE variable. The listing in Output 28.1.1has been tru[r]

variable value is less than the END= value, the series is extended with missing values. If thelast time ID variable value is greater than the END= value, the series is truncated. For example,END=“&sysdate”D uses the automatic macro variable SYSDATE to extend or truncate theseries to the curr[r]

If your input data set is not sorted in ascending order, use one of the following alternatives: Sort the data using the SORT procedure with a similar BY statement.Specify the BY statement option NOTSORTED or DESCENDING in the BY statement forthe VARMAX procedure. The NOTSORTED option does n[r]

2802 ✦ Chapter 45: Window Referenceyou know the name, you can type it in and press Return. If it is a valid choice, it will appear inthe SAS Data Sets list and will be highlighted.Time IDis the name of the ID variable for the selected input data set. To specify the ID variable, youcan type th[r]

– Forecasts and As Reported Data– United States Regional enables you to limit the range of data that is read from the time seriesenables you to specify a desired conversion frequency. Start dates are recommended on theLIBNAME statement to help you save resources when processing large databa[r]

of the depreciation schedule to the SAS session print device.Save Data Asbecomes available when you generate the depreciation schedule. Clicking it opens theSave Output Dataset dialog box where you can save the depreciation table (or portions thereof) as aSAS Dataset.OKreturns you to the Investment[r]

TRANG 1 PROC PDLREG statement,1401 PROC QLIM statement,1431 PROC SEVERITY statement,1511 PROC SIMILARITY statement,1596 PROC SIMLIN statement,1663,1670 PROC SPECTRA statement,1694 PROC S[r]

Ghi l i h m n y th nh file: assignpid.mạ à à à* H m th ba:à ứfunction pid = lsqpid(pid0,model,tspan)options=foptions;options=[1 0.01 0.01];pid=leastsq('yout_1',pid0,options,[],model,tspan);Ghi l i h m n y th nh file: lsqpid.mạ à à àB c 3/ Tr v c a s Command Windows vi t ch ng trình:ướ[r]

Analog modules Analog modules User guideUser guideLecturer: B.Eng. Tan Nguyen-HuuLecturer: B.Eng. Tan Nguyen-HuuEmail: nhtan@gmail.comEmail: nhtan@gmail.comCác module AnalogCác module AnalogEM231: 4 analog inputsEM231: 4 analog inputsEM232: 2 analog outputsEM232: 2 analog outputsEM235: 4[r]

closes the window without adding an external forecast to the project.Resetdeselects any selection made in the selection list.Factored ARIMA Model Specification WindowUse the ARIMA Model Specification window to specify an ARIMA model by using the notation:p = (lag, , lag) (lag, , lag)d = (lag, , lag)q[r]

2852 ✦ Chapter 45: Window ReferenceProduce Forecasts WindowUse the Produce Forecasts window to produce forecasts for the series in the current input data set forwhich you have fit forecasting models. Access it by using the Produce Forecasts button of the TimeSeries Forecasting window.Controls and Fie[r]

When invoked from Automatic Model Fitting, the Series to Process window shows all the numericvariables in the input data set except the time ID variable. These are the series which are currentlyavailable for model fitting.When invoked from Produce Forecasts, the Series to Process window shows all the[r]

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