Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
The Null Hypothesis - H0: There is no autocorrelation
The Alternative Hypothesis - H1: There is at least first order autocorrelation
Rejection Criteria: Reject H0 if LBQ1 >
Autocorrelation Function: RESI1
Lag ACF T LBQ
1 0.0081553 0.32 0.10
2 0.0065510 0.26 0.17
3 -0.0279832 -1.09 1.36
4 -0.0079441 -0.31 1.46
5 0.0254074 0.99 2.44
There are 83 lags but the first 5 have been used identify whether there is auto correlation present:
Lag
LBQ
Chi-Squared
Interpretation
1
0.10
= 3.84
Since LBQ = 0.10 < 3.84 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
2
0.17
= 5.99
Since LBQ = 0.17 < 5.99 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
3
1.36
= 7.81
Since LBQ = 1.36 < 7.81 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
4
1.46
= 9.48
Since LBQ = 1.46 < 9.48 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
5
2.44
= 11.07
Since LBQ = 2.44 < 11.07 so accept H0 as there is sufficient evidence to suggest there is no autocorrelation
Matching distribution is a probability distribution which arises in the following manner. Suppose that the set of n subjects, numbered 1; . . . ; n respectively, are arranged in
Balanced incomplete block design : A design in which all the treatments are not used in all blocks. Such designs have the below stated properties: * each block comprises the
I do have a data of real gdp for each state and from 2000 to 2010 and I also have estimated population of illigel immigrants for each state from 2000 to 2010. In my thesis I am try
Classification and regression tree technique (CART): The alternative to the multiple regression and associated techniques or methods for determining subsets of the explanatory va
The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
An oil company thinks that there is a 60% chance that there is oil in the land they own. Before drilling they run a soil test. When there is oil in the ground, the soil test comes
The problematic and enigmatic theory of an inference introduced by the Fisher, which extracts a probability distribution for the parameter on the basis of the data without having f
elements , importance, limitation, and theories
1) Consider an antenna with a pattern: G(θ,φ) = sinn(θ/θ0) cos(θ/θ0) where θ0 = Π/1.5 (a) What is the 3-dB bandwidth? (b) What is the 10-dB beam width? (c) What is t
Length-biased data is a data which arise when the probability that an item is sampled is proportional to its own length. A main example of this situation occurs in the renewal the
Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd