- #Test for cointegration xlstat full#
- #Test for cointegration xlstat software#
- #Test for cointegration xlstat series#
VEC( q) model are not uniquely identified, though their product C = A B′ is. The parameters A and B in the reduced-rank
#Test for cointegration xlstat full#
Inference is that C has full rank, and y t is stationary in levels. If jcitest rejectsĪll cointegration ranks r less than numDims, the Is zero, and the VEC( q) model reduces to a standard If jcitest fails to reject the null of cointegration rank r = 0, the inference is that the error-correction coefficient C You can further access the fields of the structure using dot notation,įor example, enter mles.r n( m).paramNames for To access results stored in mles, for example, Variables of mles correspond to different, maintainedġ.
Rows of mles correspond to tests specified Unrestricted loglikelihood of Y under the Obtained by fitting the VEC( q) model of y t toĮstimated covariance Q of the innovationsĮigenvector associated with the eigenvalue in eigVal.Įigenvectors v are normalized so that v′ S 11 v = 1, where S 11 is Of residuals, where T is the effective sample size, Structure of parameter estimates with field names corresponding To access results stored in cValue, for example,Īrray of structures of maximum likelihood estimates associated withĬell vector of parameter names, of the form: Variables of cValue correspond to different, maintainedġ. Rows of cValue correspond to tests specified Values were computed using methods described in. Then linearly interpolates test-critical values from the tables.
Tables of critical values from the file Data_JCITest.mat, To access results stored in stat, for example,Īrray of critical values for right-tail probabilities, determinedīy the alpha name-value pair argument. Variables of stat correspond to different, maintainedġ. Rows of stat correspond to tests specified To access results stored in pValue, for example,Īrray of test statistics, determined by the test name-value Variables of pValue correspond to different, maintainedġ.
#Test for cointegration xlstat software#
Rows of pValue correspond to tests specifiedīy the input arguments, and the software labels the rows t1, t2., t u, Values of h equal to 0 ( false)Īrray of right-tail probabilities of the test statistics. Indicate rejection of the null of cointegration rank r inįavor of the alternative. To access results stored in h, for example, Variables of h correspond to different, maintainedġ, and the software labels the variables r0, r1., r R,ġ. The input arguments, and the software labels the rows t1, t2., t u, Rows of h correspond to tests specified by Vector values must have equal length.Īrray of Boolean decisions for the tests. paramVals forĬharacter vectors values are expanded to the length of any vector Displayed parameter values are returned in mles.rn( m). This display is only available if jcitest isĬalled with five output arguments (that is, if mles isĬomputed). This is the default if jcitest isĬalled with more than one output argument (that is, if pValue isĬomputed), and is unavailable if jcitest is calledĭisplay maximum likelihood estimates of the parameter valuesĪssociated with the reduced-rank VEC( q) model of y t. Multiple testsĪre displayed in separate summaries. Null ranks r = 0: numDims −ġ are displayed in the first column of each summary. This is the default if jcitest isĬalled with only one output argument ( h).ĭisplay a summary of test results.
Ordered estimates of the eigenvalues of C = A B′, λ 1 > StatisticsĪre computed using the effective sample size T and Both tests assessĬointegration rank less than or equal to r. Vector of character vectors indicating the type of test to be performed. The effective sample size is T = N−( q+1).Ĭharacter vector, such as 'trace', or cell
#Test for cointegration xlstat series#
Lagging and differencing a time series reduce the sample size.ĭifferences, the common time base is q+2: N and Lagged differences in the VEC( q) model of y t. Scalar or vector of nonnegative integers indicating the number q of Linear regression coefficients, respectively, onto the orthogonal complement of There are intercepts and linear trends in the cointegrated series and there are deterministic quadratic trends in the levels of the data.ĭeterministic terms outside of the cointegrating relations,ĭ 1, are identified by projecting constant and There are intercepts and linear trends in the cointegrated series and there are deterministic linear trends in the levels of the data.Ī( B´ y t−1+ c 0+ d 0 t)+ c 1+ d 1 t. This is the default value.Ī( B´ y t−1+ c 0+ d 0 t)+ c 1. There are intercepts in the cointegrated series and there are deterministic linear trends in the levels of the data. There are intercepts in the cointegrated series and there are no deterministic trends in the levels of the data.Ī( B´ y t−1+ c 0)+ c 1. There are no intercepts or trends in the cointegrated series and there are no deterministic trends in the levels of the data.Ī( B´ y t−1+ c 0).
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