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create u 1 11 !k=1 2 'Paso 2: Hallamos la varianza scalar teta1=0. scalar mu= scalar sigmacuadmu= scalar s= scalar varianza= sigmacuadmu(1+teta1^2) 'Paso 3: Hallamos la Función de Autocovarianza vector (!k) FACOV for !count = 1 to !k if !count= s then FACOV(!count)= - 1teta1sigmacuadmu endif if !count >s then FACOV(!count)= 0 endif if !count < s then FACOV(!count)= 0 endif next 'Paso 4: Hallamos la Función de Autocorrelación vector (!k) FA for !count = 1 to !k if !count= s then FA(!count)= - teta1/(1+teta1^2) endif if !count >s then FA(!count)= 0 endif if !count < s then FA(!count)= 0 endif next 'Paso 5: Hallamos la Autocorrelación Parcial vector (!k) FAP for !count = 1 to !k if !count=s then FAP(!count)= FA(!count) endif if !count = s+4 then FAP(!count)= (-teta1^(!count))(1- teta1^2)/(1-teta1^(2((!count)+1))) endif if !count = s+8 then FAP(!count)= (-teta1^(!count))(1- teta1^2)/(1-teta1^(2*((!count)+1))) endif next
EJERCICIO 9.
create u 1 1 1 !k= 'Paso 2: Hallamos la varianza scalar teta1=-0. scalar mu= scalar sigmacuadmu= scalar s= scalar varianza= sigmacuadmu(1+teta1^2) 'Paso 3: Hallamos la Función de Autocovarianza vector (!k) FACOV for !count = 1 to !k if !count= s then FACOV(!count)= - 1teta1sigmacuadmu endif if !count >s then FACOV(!count)= 0 endif if !count < s then FACOV(!count)= 0 endif next 'Paso 4: Hallamos la Función de Autocorrelación vector (!k) FA for !count = 1 to !k if !count= s then FA(!count)= - teta1/(1+teta1^2) endif if !count >s then FA(!count)= 0 endif if !count < s then FA(!count)= 0 endif next 'Paso 5: Hallamos la Autocorrelación Parcial vector (!k) FAP for !count = 1 to !k if !count=s then FAP(!count)= FA(!count) endif if !count = s+4 then FAP(!count)= (-teta1^(2))(1-teta1^2)/(1- teta1^(6)) endif if !count = s+8 then FAP(!count)= (-teta1^(3))*(1-teta1^2)/(1- teta1^(8)) endif next
EJERCICIO 9.
create u 1 11 !k= 'Paso 1: Hallamos la varianza scalar teta1=0. scalar teta2=0. scalar mu= scalar s= scalar sigmacuadmu= scalar varianza= sigmacuadmu*(1+teta1^2+teta2^2) 'Paso 2: Hallamos la Función de Autocovarianza
vector (!k) FACOV for !count = 1 to !k if !count=s then FACOV(!count)= (- 1teta1+teta1teta2)sigmacuadmu endif if !count=2s then FACOV(!count)= - 1teta2sigmacuadmu endif if !count>2s then FACOV(!count)= 0 endif next 'Paso 3: Hallamos la Función de Autocorrelación vector (!k) FA for !count = 1 to !k if !count=s then FA(!count)= (- teta1+teta1teta2)/(1+teta1^2+teta2^2) endif if !count=2s then FA(!count)= - 1teta2/(1+teta1^2+teta2^2) endif if !count>2s then FA(!count)= 0 endif next 'Paso 4: Hallamos la Autocorrelación Parcial vector(!k) fi vector fi(1)=FA(1) matrix (!k,!k) phi vector FA=FA vector (!k-1) w vector (!k-1) z scalar w scalar z matrix (!k-1,!k-1) s matrix (!k-1,!k-1) s matrix phi(1,1)=FA(1) vector (!k) phicol phicol(1)=FA(1) for !j=1 to !k- 1 for !i=1 to !j s1(!j,!i)=phi(!j,!i)FA(!j+1-!i) s2(!j,!i)=phi(!j,!i)FA(!i) next for !i=1 to !j w(!j)=w0+ s1(!j,!i) w0=w(!j) z(!j)= z0+s2(!j,!i) z0=z(!j) next phi(!j+1,!j+1)=(FA(!j+1)- w(!j))/(1-z(!j)) phicol(!j+1)=phi(!j+1, !j+1) for !i=1 to !j phi(!j+1,!i)=phi(!j,!i)- phi(!j+1,!j+1)phi(!j,!j+1-!i) next w0= z0= next show fa.spike show phicol.spike EJERCICIO 9. create u 1 11 !k= 'Paso 1: Hallamos la varianza scalar teta1=-0. 7 scalar teta2=0. 2 scalar mu= scalar s= scalar sigmacuadmu= scalar varianza= sigmacuadmu(1+teta1^2+teta2^2) 'Paso 2: Hallamos la Función de Autocovarianza vector (!k) FACOV for !count = 1 to !k if !count=s then FACOV(!count)= (- 1teta1+teta1teta2)sigmacuadmu endif if !count=2s then FACOV(!count)= - 1teta2sigmacuadmu endif if !count>2s then FACOV(!count)= 0 endif next 'Paso 3: Hallamos la Función de Autocorrelación vector (!k) FA for !count = 1 to !k if !count=s then FA(!count)= (- teta1+teta1teta2)/(1+teta1^2+teta2^2) endif if !count=2s then FA(!count)= - 1teta2/(1+teta1^2+teta2^2) endif if !count>2s then FA(!count)= 0 endif next 'Paso 4: Hallamos la Autocorrelación Parcial vector(!k) fi vector fi(1)=FA(1) matrix (!k,!k) phi vector FA=FA vector (!k-1) w vector (!k-1) z scalar w scalar z matrix (!k-1,!k-1) s
FACOV(!count)= (teta1)sigmacuadmu/(1- teta1^2) endif if !count =s+4 then FACOV(!count)= ((teta1)^2)sigmacuadmu/(1-teta1^2) endif if !count =s+8 then FACOV(!count)= ((teta1)^3)sigmacuadmu/(1-teta1^2) endif if !count >3s then FACOV(!count)= 0 endif next 'Paso 4: Hallamos la Función de Autocorrelación vector (!k) FA for !count = 1 to !k if !count =s then FA(!count)= teta1^(1) endif if !count =s+4 then FA(!count)= teta1^(2) endif if !count =s+8 then FA(!count)= teta1^(3) endif if !count >3*s then FA(!count)= 0 endif next 'Paso 5: Hallamos la Autocorrelación Parcial vector (!k) FAP for !count = 1 to !k if !count=s then FAP(!count)= FA(!count) endif if !count>s then FAP(!count)= endif next
EJERCICIO 9.
create u 1 11 !k= 'Paso 2: Hallamos la varianza scalar teta1=-0. scalar cons= scalar s= scalar sigmacuadmu= scalar varianza= sigmacuadmu/(1-teta1^2) scalar mu=cons/(1-teta1) 'Paso 3: Hallamos la Función de Autocovarianza vector (!k) FACOV for !count = 1 to !k if !count =s then FACOV(!count)= (teta1)sigmacuadmu/(1- teta1^2) endif if !count =2s then FACOV(!count)= ((teta1)^2)sigmacuadmu/(1-teta1^2) endif if !count =3s then FACOV(!count)= ((teta1)^3)sigmacuadmu/(1-teta1^2) endif if !count >3s then FACOV(!count)= 0 endif next 'Paso 4: Hallamos la Función de Autocorrelación vector (!k) FA for !count = 1 to !k if !count =s then FA(!count)= teta1^(1) endif if !count =2s then FA(!count)= teta1^(2) endif if !count =3s then FA(!count)= teta1^(3) endif if !count >3s then FA(!count)= 0 endif next 'Paso 5: Hallamos la Autocorrelación Parcial vector (!k) FAP for !count = 1 to !k if !count=s then FAP(!count)= FA(!count) endif if !count>s then FAP(!count)= endif next EJERCICIO 9. create u 1 11 scalar k= !k= !p= 'Ejercicio 9. scalar teta1=0. scalar teta2= 0. scalar delta= scalar sigmacuadmu= scalar x= scalar varianza= ((1- teta2)/(1+teta2))((sigmacuadmu)/((1-teta1- teta2)(1+teta1-teta2))) scalar mu=delta/(1-teta1-teta2) ' Hallando la Función de Autocovarianza FACOV vector (!p) FACOV for !count =1 to !p if !count=0 then FACOV(!count)= 4. endif if !count=1x then FACOV(!count)= 2. endif if !count=2x then FACOV(!count)= 2. Endif if !count=3x then
FACOV(!count)= teta1facov(!count- 4)+teta2facov(!count-8) Endif if !count=4x then FACOV(!count)= teta1facov(!count- 4)+teta2facov(!count-8) Endif if !count=5x then FACOV(!count)= teta1facov(!count- 4)+teta2facov(!count-8) Endif if !count=6x then FACOV(!count)= teta1facov(!count- 4)+teta2facov(!count-8) Endif if !count=7x then FACOV(!count)= teta1facov(!count- 4)+teta2facov(!count-8) endif next ' Hallando la Función de Autocorrelacion vector(k) FA for !count = 1 to k if !count=4 then FA(!count)= teta1/(1-teta2) endif if !count=8 then FA(!count)= teta1FA(4)+teta endif if !count=12 then FA(!count)= teta1FA(8)+teta2FA(4) endif if !count>12 then FA(!count)= 0 endif next 'hnnjnj matrix (!k,!k) phi vector (!k-1) w vector (!k-1) z scalar w scalar z matrix (!k-1,!k-1) s matrix (!k-1,!k-1) s matrix phi(1,1)=FA(1) vector (!k) phicol phicol(1)=FA(1) for !j=1 to !k- 1 for !i=1 to !j s1(!j,!i)=phi(!j,!i)FA(!j+1-!i) s2(!j,!i)=phi(!j,!i)FA(!i) next for !i=1 to !j w(!j)=w0+ s1(!j,!i) w0=w(!j) z(!j)= z0+s2(!j,!i) z0=z(!j) next phi(!j+1,!j+1)=(FA(!j+1)- w(!j))/(1-z(!j)) phicol(!j+1)=phi(!j+1, !j+1) for !i=1 to !j phi(!j+1,!i)=phi(!j,!i)- phi(!j+1,!j+1)phi(!j,!j+1-!i) next w0= z0= next show fa.spike show phicol.spike EJERCICIO 9. create u 1 11 scalar k= !k= 'Ejercicio 9. scalar teta1=-1. scalar teta2= - 0. scalar mu= scalar sigmacuadmu= scalar x= vector(k) FA for !count = 1 to k if !count=4 then FA(!count)= teta1/(1-teta2) endif if !count=8 then FA(!count)= teta1FA(4)+teta endif if !count=12 then FA(!count)= teta1FA(8)+teta2FA(4) endif if !count>12 then FA(!count)= 0 endif next 'hnnjnj matrix (!k,!k) phi vector (!k-1) w vector (!k-1) z scalar w scalar z matrix (!k-1,!k-1) s matrix (!k-1,!k-1) s matrix phi(1,1)=FA(1) vector (!k) phicol phicol(1)=FA(1) for !j=1 to !k- 1 for !i=1 to !j s1(!j,!i)=phi(!j,!i)FA(!j+1-!i) s2(!j,!i)=phi(!j,!i)FA(!i) next for !i=1 to !j w(!j)=w0+ s1(!j,!i) w0=w(!j) z(!j)= z0+s2(!j,!i) z0=z(!j) next phi(!j+1,!j+1)=(FA(!j+1)- w(!j))/(1-z(!j)) phicol(!j+1)=phi(!j+1, !j+1) for !i=1 to !j phi(!j+1,!i)=phi(!j,!i)- phi(!j+1,!j+1)phi(!j,!j+1-!i) next w0= z0= next show fa.spike show phicol.spike
