Throughout, β₯ β
β₯ 2 \lVert\cdot\rVert_{2} β₯ β
β₯ 2 β and β¨ β
, β
β© 2 \langle\cdot,\cdot\rangle_{2} β¨ β
, β
β© 2 β are the mean-square norm and inner product of Square-Integrable Random Variables and the Mean-Square Inner Product .
Claim 1. By the definitions of the dot product and the matrix-vector product , applied pointwise on Ξ© \Omega Ξ© ,
Y β
( M Y ) = β i = 1 p β j = 1 p M i j β Y i Y j . Y\cdot(MY)=\sum_{i=1}^{p}\sum_{j=1}^{p}M_{ij}\,Y^{i}Y^{j}. Y β
( M Y ) = i = 1 β p β j = 1 β p β M ij β Y i Y j .
For each pair ( i , j ) (i,j) ( i , j ) the product Y i Y j Y^{i}Y^{j} Y i Y j is integrable with E [ β£ Y i Y j β£ ] β€ β₯ Y i β₯ 2 β₯ Y j β₯ 2 \mathbb{E}\bigl[|Y^{i}Y^{j}|\bigr]\le\lVert Y^{i}\rVert_{2}\lVert Y^{j}\rVert_{2} E [ β£ Y i Y j β£ ] β€ β₯ Y i β₯ 2 β β₯ Y j β₯ 2 β , by Cauchy-Schwarz and Triangle Inequalities for the Mean-Square Norm applied to β£ Y i β£ |Y^{i}| β£ Y i β£ and β£ Y j β£ |Y^{j}| β£ Y j β£ , which are square-integrable by the closure properties of Square-Integrable Random Variables and the Mean-Square Inner Product (their squares agree with those of Y i , Y j Y^{i},Y^{j} Y i , Y j ). Hence the finite sum is integrable and, by linearity of the integral (Linearity and Monotonicity of the Lebesgue Integral ),
E [ Y β
( M Y ) ] = β i , j M i j β E [ Y i Y j ] . \mathbb{E}\bigl[Y\cdot(MY)\bigr]=\sum_{i,j}M_{ij}\,\mathbb{E}[Y^{i}Y^{j}]. E [ Y β
( M Y ) ] = i , j β β M ij β E [ Y i Y j ] .
By the definition of the covariance , E [ Y i Y j ] = Cov β‘ ( Y i , Y j ) + E [ Y i ] E [ Y j ] = C i j + ΞΌ i ΞΌ j \mathbb{E}[Y^{i}Y^{j}]=\operatorname{Cov}(Y^{i},Y^{j})+\mathbb{E}[Y^{i}]\mathbb{E}[Y^{j}]=C_{ij}+\mu^{i}\mu^{j} E [ Y i Y j ] = Cov ( Y i , Y j ) + E [ Y i ] E [ Y j ] = C ij β + ΞΌ i ΞΌ j . Therefore
E [ Y β
( M Y ) ] = β i , j M i j C i j + β i , j M i j ΞΌ i ΞΌ j = tr β‘ ( M β€ C ) + ΞΌ β
( M ΞΌ ) , \mathbb{E}\bigl[Y\cdot(MY)\bigr]=\sum_{i,j}M_{ij}C_{ij}+\sum_{i,j}M_{ij}\mu^{i}\mu^{j}=\operatorname{tr}(M^{\top}C)+\mu\cdot(M\mu), E [ Y β
( M Y ) ] = i , j β β M ij β C ij β + i , j β β M ij β ΞΌ i ΞΌ j = tr ( M β€ C ) + ΞΌ β
( M ΞΌ ) ,
using claim 4 of Basic Properties of the Trace for the first sum and the definitions of dot product and matrix-vector product for the second. Finally, C C C is symmetric (Cov β‘ ( Y i , Y j ) = Cov β‘ ( Y j , Y i ) \operatorname{Cov}(Y^{i},Y^{j})=\operatorname{Cov}(Y^{j},Y^{i}) Cov ( Y i , Y j ) = Cov ( Y j , Y i ) by the symmetry of its defining formula), so claims 2-3 of Basic Properties of the Trace give tr β‘ ( M β€ C ) = tr β‘ ( ( M β€ C ) β€ ) = tr β‘ ( C β€ M ) = tr β‘ ( C M ) = tr β‘ ( M C ) \operatorname{tr}(M^{\top}C)=\operatorname{tr}\bigl((M^{\top}C)^{\top}\bigr)=\operatorname{tr}(C^{\top}M)=\operatorname{tr}(CM)=\operatorname{tr}(MC) tr ( M β€ C ) = tr ( ( M β€ C ) β€ ) = tr ( C β€ M ) = tr ( CM ) = tr ( MC ) , with ( M β€ C ) β€ = C β€ M (M^{\top}C)^{\top}=C^{\top}M ( M β€ C ) β€ = C β€ M by claim 3 of Componentwise Estimates, Transpose Identities, and Indefinite Riemann Integrals .
Claim 2. As in claim 1, for each t t t ,
E [ Y t β
( M ( t ) Z t ) ] = β i = 1 p β j = 1 q M i j ( t ) β E [ Y t i Z t j ] , \mathbb{E}\bigl[Y_t\cdot(M(t)Z_t)\bigr]=\sum_{i=1}^{p}\sum_{j=1}^{q}M_{ij}(t)\,\mathbb{E}[Y^{i}_tZ^{j}_t], E [ Y t β β
( M ( t ) Z t β ) ] = i = 1 β p β j = 1 β q β M ij β ( t ) E [ Y t i β Z t j β ] ,
all terms defined and finite. It therefore suffices, by the continuity of sums and products of continuous real-valued functions on [ a , b ] [a,b] [ a , b ] (claims 2 and 3 of Continuity of Sums and Products of Real-Valued Functions on a Metric Space at each point, then claim 5 of that theorem, with [ a , b ] [a,b] [ a , b ] and R \mathbb{R} R carrying the metric of the real line ), to show that each function t β¦ E [ Y t i Z t j ] = β¨ Y t i , Z t j β© 2 t\mapsto\mathbb{E}[Y^{i}_tZ^{j}_t]=\langle Y^{i}_t,Z^{j}_t\rangle_{2} t β¦ E [ Y t i β Z t j β ] = β¨ Y t i β , Z t j β β© 2 β is continuous on [ a , b ] [a,b] [ a , b ] . Fix s , t β [ a , b ] s,t\in[a,b] s , t β [ a , b ] . Adding and subtracting E [ Y s i Z t j ] \mathbb{E}[Y^{i}_sZ^{j}_t] E [ Y s i β Z t j β ] and applying Cauchy-Schwarz and Triangle Inequalities for the Mean-Square Norm twice,
β£ E [ Y t i Z t j ] β E [ Y s i Z s j ] β£ β€ β₯ Y t i β Y s i β₯ 2 β β₯ Z t j β₯ 2 + β₯ Y s i β₯ 2 β β₯ Z t j β Z s j β₯ 2 . \bigl|\mathbb{E}[Y^{i}_tZ^{j}_t]-\mathbb{E}[Y^{i}_sZ^{j}_s]\bigr|\le\lVert Y^{i}_t-Y^{i}_s\rVert_{2}\,\lVert Z^{j}_t\rVert_{2}+\lVert Y^{i}_s\rVert_{2}\,\lVert Z^{j}_t-Z^{j}_s\rVert_{2}. β E [ Y t i β Z t j β ] β E [ Y s i β Z s j β ] β β€ β₯ Y t i β β Y s i β β₯ 2 β β₯ Z t j β β₯ 2 β + β₯ Y s i β β₯ 2 β β₯ Z t j β β Z s j β β₯ 2 β .
By claim 4 of Basic Properties of the Mean-Square Riemann Integral , the functions t β¦ β₯ Y t i β₯ 2 t\mapsto\lVert Y^{i}_t\rVert_{2} t β¦ β₯ Y t i β β₯ 2 β and t β¦ β₯ Z t j β₯ 2 t\mapsto\lVert Z^{j}_t\rVert_{2} t β¦ β₯ Z t j β β₯ 2 β are continuous on the compact interval [ a , b ] [a,b] [ a , b ] , hence bounded there by Extreme Value Theorem on a Closed Real Interval ; and β₯ Y t i β Y s i β₯ 2 β 0 \lVert Y^{i}_t-Y^{i}_s\rVert_{2}\to0 β₯ Y t i β β Y s i β β₯ 2 β β 0 , β₯ Z t j β Z s j β₯ 2 β 0 \lVert Z^{j}_t-Z^{j}_s\rVert_{2}\to0 β₯ Z t j β β Z s j β β₯ 2 β β 0 as t β s t\to s t β s by mean-square continuity . Hence the right-hand side tends to 0 0 0 as t β s t\to s t β s , which is the asserted continuity at s s s . β‘ \square β‘