Simulate 100 observations from an ARMA(1,1) model and
another 30 observations from an ARMA(1,1) model both with = 0.8 and
= 0.3.
please use Rstudio and provide the codes.
1. Why are (1) statistical inference, (2) predictive statistics,
(3) prescriptive statistics, and (4) descriptive statistics methods
important to Six Sigma?
Describe the structure of a cause-and-effect diagram.
What is a root cause? How does the “5 Why” technique help
uncover the root cause?
Use the classical model to derive a formula for the electron’s
kenetic energy as a function of its orbital distance, assuming the
electron is in a circular orbit. In other words, derive a formula
that you could use to calculate the kinetic energy of the electron
if you knew its orbital distance.
What would be the formula for the electron's kinetic energy K in
terms of the orbital distance d.
Using R:
1. Generate AR(1), AR(2), MA(1), MA(2), and ARMA(1,1) processes
with different parameter values, and draw ACF and PACF. Discuss the
characteristics of ACF snd PACF for these processes.
2. Generate AR(1) process {X_t}. Compute the first difference
Y_t = X_t - X_(t-1). Draw ACF and PACF of {Y_t}. What can you say
about this process? Is it again a AR(1) process? What can you say
in general?
3.For the AR(2) processes with the following parameters,
determine if AR(2)...
1) Once we have a forecasting model, the specific units of
measurement used in the model are
A)
expressed in units of production for long-range plans.
B)
expressed in units of production to determine future requirements
for plant and equipment.
C)
the same for every area of the business.
D)
expressed in job descriptions for human resource planners.
`E)
All of the above are correct
1. Derive each mathematical model of projectile motion and
compare each part of derive, ( projectile motion only, projectile
motion with wind force, projectile motion with wind force and
projectile motion with wind force and air resistance) Note of sign
of velocity Y as indicate go up or down.
(a)projectile motion
Derive the mathematical model (in 2D) using Newton’s 2nd Law and
produce the ODEs (ordinary differential equation) involving the
horizontal and vertical velocities respectively. Solve for the
velocities using...
Consider the following ARMA(1,1) process
(1 − 0.3B)Xt = (1 − 0.2B)Zt
where{Zi}∼WN(0,σ^2)withE(Z1)=0andVar(Z1)=σ^2 <∞.
(i) Discuss if the process has a causal stationary solution.
(ii) Find an MA(∞) representation for Xt.
(iii) Find the autocorrelation function for the process
{Xt}.
Assignment III 1) Use the non-machine formula to calculate the
variance and standard deviation from the following data Herd 1 67
62 69 72 68 68 71 69 65 71 70 64 64 66 71 67 75 2) What is the
probability that one card selected from a deck of 52 is a club or a
number card or both? 3) A container contains 10 green tennis balls
and 7 orange tennis balls. What is the probability of drawing 2...