# Large deviations for randomly weighted sums with dominantly varying tails and widely orthant dependent structure

## Abstract

We prove large deviation inequalities for the randomly weighted partial and random sums $S n θ = ∑ i = 1 n θ i X i$, $n≥1$; $S c θ (t)= ∑ i = 1 N ( t ) ( θ i X i +c)$, $c∈R$, where ${N(t),t≥0}$ is a counting process, ${ θ i ,i≥1}$ is a sequence of positive random variables with two-sided bounds, and ${ X i ,i≥1}$ is a sequence of non-identically distributed real-valued random variables, while the three random sources above are mutually independent. Special attention is paid to the distribution of dominated variation and the widely orthant dependence structure.

MSC:62E20, 62H20, 62P05.

## 1 Introduction

Let ${ X k ,k≥1}$ be a sequence of real-valued random variables (r.v.s) with $X k$’s distribution function (d.f.) $F k (x)=1− F ¯ k (x)$ and $μ k =E X k =0$ for every $k≥1$, and ${ θ k ,k≥1}$ be another sequence of positive random variables, satisfying $P r (a≤ θ k ≤b)=1$, $k≥1$, where $0. ${N(t),t≥0}$ denotes a counting process (that is, a non-negative, non-decreasing, and integer-valued stochastic process) with a finite mean function $λ(t)$ for $t≥0$ and $λ(t)→∞$ as $t→∞$. Besides, the three random sources above are mutually independent. Denote $S n θ = ∑ i = 1 n θ i X i$, $n≥1$ and $S c θ (t)= ∑ i = 1 N ( t ) ( θ i X i +c)$, $t≥0$, $c∈R$. By convention, the summation over an empty set of indices produces a value of 0. In the present paper, we are interested in the probabilities of large deviations of ${ S n θ }$ and ${ S c θ (t)}$ in the situation that ${ X k ,k≥1}$ are heavy-tailed and widely orthant dependent.

Since the theory of large deviations with heavy tails is widely used in insurance and finance, in recent decades, there have been a series of articles devoted to related problems. For more details, please refer to Embrechts et al., Klüppelberg and Mikosch , Mikosch and Nagaev  and references therein. Recently Tang  extended the asymptotic behavior of large deviation probabilities of partial sums of heavy-tailed random variables to the case of negatively dependent ones. Under the assumption that random variables are non-identically distributed and extended negatively dependent, Liu  obtained a result similar to the one in the above paper, which was promoted to random sums in various situations later by Chen et al.. Specially, Shen and Lin  investigated large deviations of randomly weighted partial sums with negatively dependent and consistently varying-tailed random variables, but, unfortunately, there are some flaws in their proofs.

In this paper, motivated by the work of Liu and Hu  and Chen et al., on the one hand, we aim to prove that for each fixed $γ>0$, there exist positive constant $M 1$ and $M 2$ such that the inequalities

$P r ( S n θ > x ) ≥ M 1 ( 1 + o ( 1 ) ) ∑ k = 1 n P r ( θ k X k >x)$
(1.1)

and

$P r ( S n θ > x ) ≤ M 2 ( 1 + o ( 1 ) ) ∑ k = 1 n P r ( θ k X k >x)$
(1.2)

hold uniformly for all $x≥γn$ as $n→∞$, respectively; on the other hand, for arbitrarily fixed $γ>c$ (c is an arbitrarily given real number), there are positive constant $M ˜ 1$ and $M ˜ 2$ such that

$P r ( S c θ ( t ) > x ) ≥ M ˜ 1 ( 1 + o ( 1 ) ) E [ ∑ k = 1 N ( t ) P r ( θ k X k > x − c λ ( t ) ) ]$
(1.3)

and

$P r ( S c θ ( t ) > x ) ≤ M ˜ 2 ( 1 + o ( 1 ) ) E [ ∑ k = 1 N ( t ) P r ( θ k X k > x − c λ ( t ) ) ]$
(1.4)

hold uniformly for all $x≥γλ(t)$ as $t→∞$, respectively.

The paper is organized as follows. Section 2 presents our main results after recalling some preliminaries. Sections 3 and 4 prove Theorems 2.1 and 2.2, respectively.

## 2 Main results

We say that a random variable X or its distribution function is heavy-tailed if $E e t X =∞$ for all $t>0$. An important class of heavy-tailed distributions is , which consists of all distributions with dominated variation in the sense that the relation $lim sup x → ∞ F ¯ (xy)/ F ¯ (x)<∞$ holds for some (hence for all) $0. Recall the upper/lower Matuszewska index of distribution F, defined as $J F + =− lim y → ∞ (log F ¯ ∗ (y)/logy)$ and $J F − =− lim y → ∞ (log F ¯ ∗ (y)/logy)$, where $F ¯ ∗ (y)= lim inf x → ∞ F ¯ (xy)/ F ¯ (x)$ and $F ¯ ∗ (y)= lim sup x → ∞ F ¯ (xy)/ F ¯ (x)$ for any $y>0$. From Lemma 3.5 of Tang and Tsitsiashvili , we know that if $F∈D$, then $0≤ J F − ≤ J F + <∞$, and for arbitrary $p 1 < J F −$ and $p 2 > J F +$, there exist positive constant $C ˜ i$ and $D ˜ i$, $i=1,2$, such that

$F ¯ (y)/ F ¯ (x)≥ C ˜ 1 ( x / y ) p 1$
(2.1)

holds for all $x≥y≥ D ˜ 1$, and

$F ¯ (y)/ F ¯ (x)≤ C ˜ 2 ( x / y ) p 2$
(2.2)

holds for all $x≥y≥ D ˜ 2$. Hence, for any $p 1 < J F −$, we have

$F ¯ (x)=o ( x − p 1 ) ;$
(2.3)

and for any $p 2 > J F +$,

$x − p 2 =o ( F ¯ ( x ) ) .$
(2.4)

Furthermore, if the distribution $F + (x)=F(x) 1 ( x ≥ 0 )$ has a finite mean, then $J F + ≥1$.

Now, we present some new dependence structures introduced in Wang et al..

Definition 2.1 We say that the r.v.s ${ η n ,n≥1}$ are widely upper orthant dependent (WUOD) if there exists a finite real sequence ${ g U (n),n≥1}$ satisfying for each $n≥1$ and for all $x i ∈(−∞,+∞)$, $1≤i≤n$,

$P r ( ⋂ i = 1 n { η i > x i } ) ≤ g U (n) ∏ i = 1 n P r ( η i > x i );$
(2.5)

we say that the r.v.s ${ η n ,n≥1}$ are widely lower orthant dependent (WLOD) if there exists a finite real sequence ${ g L (n),n≥1}$ satisfying for each $n≥1$ and for all $x i ∈(−∞,+∞)$, $1≤i≤n$,

$P r ( ⋂ i = 1 n { η i ≤ x i } ) ≤ g L (n) ∏ i = 1 n P r ( η i ≤ x i );$
(2.6)

if they are both WUOD and WLOD, then we say that the r.v.s ${ η n ,n≥1}$ are widely orthant dependent (WOD). WUOD, WLOD, and WOD r.v.s are called, by a joint name, wide dependence (WD) r.v.s, and $g U (n)$, $g L (n)$, $n≥1$, are called dominating coefficients.

Wang et al. also gave some examples of WD r.v.s with various dominating coefficients which show that WD r.v.s contain some common negatively dependent r.v.s, some positively dependent r.v.s and some others.

From the definitions of WD, the following proposition can be obtained directly (see, e.g., Wang et al.).

Proposition 2.1 (1) Let${ η n ,n≥1}$be WUOD (WLOD) with dominating coefficients$g U (n)$, $n≥1$ ($g L (n)$, $n≥1$). If${ f n (⋅),n≥1}$are non-decreasing, then${ f n ( η n ),n≥1}$are still WUOD (WLOD) with dominating coefficients$g U (n)$, $n≥1$ ($g L (n)$, $n≥1$); if${ f n (⋅),n≥1}$are non-increasing, then${ f n ( η n ),n≥1}$are WLOD (WUOD) with dominating coefficients$g U (n)$, $n≥1$ ($g L (n)$, $n≥1$).

(2) If${ η n ,n≥1}$are non-negative and WUOD with dominating coefficients$g U (n)$, $n≥1$, then for each$n≥1$,

$E ∏ i = 1 n η i ≤ g U (n) ∏ i = 1 n E η i .$

In particular, if${ η n ,n≥1}$are WUOD with dominating coefficients$g U (n)$, $n≥1$, then for each$n≥1$and any$s>0$,

$Eexp { s ∑ i = 1 n η i } ≤ g U (n) ∏ i = 1 n Eexp{s η i }.$

For convenience, we introduce some notation. For two positive functions $a(⋅)$ and $b(⋅)$, we write $a(t)≍b(t)$ if $0< lim inf t → ∞ a(t)/b(t)≤ lim sup t → ∞ a(t)/b(t)<∞$. For two positive bivariate functions $a(⋅,⋅)$ and $b(⋅,⋅)$, we say that the asymptotic relation $a(n,x)≲b(n,x)$ or $a(n,x)≳b(n,x)$ holds uniformly over all x in a nonempty set Δ, if $lim sup n → ∞ sup x ∈ Δ a(n,x)/b(n,x)≤1$ or $lim inf n → ∞ inf x ∈ Δ a(n,x)/b(n,x)≥1$. For a real number x, we write $x + =max{x,0}$ and $x − =−min{x,0}$.

Before we state our main results, we will introduce some basic assumptions, to be used in this paper.

(A1) There exist a real-valued random variable Y with its d.f. $F Y (x)∈D$, and some positive integer $n 0$, positive constants $C 1$ and T such that for all $n> n 0$,

$1 n ∑ i = 1 n F ¯ i (x)≥ C 1 F ¯ Y (x),$
(2.7)

holds uniformly for all $x≥T$, and $E ( Y + ) s <∞$ for some $s>1$.

(A2) There exist a real-valued random variable Z with its d.f. $F Z (x)∈D$, and positive constants $C 2$, $C 3$ and T such that for every $n≥1$,

$1 n ∑ i = 1 n F ¯ i (x)≤ C 2 F ¯ Z (x)$
(2.8)

holds uniformly for all $x≥T$, and for n large enough,

$1 n ∑ i = 1 n F i (x)≤ C 3 F Z (x)$
(2.9)

holds uniformly for all $x≤−T$; and $EZ<∞$, $J F Z − >1$.

(A3)

$lim sup x → ∞ F ¯ Z (x)/ F ¯ Y (x)<∞.$
(2.10)

(A4)

$F Z (−x)=o ( F ¯ Y ( x ) ) .$
(2.11)

Remark 2.1 According to (2.7), (2.8), and (2.10), we can see that the r.v. Z’s and Y’s right tails are weak equivalent, i.e., $F ¯ Z (x)≍ F ¯ Y (x)$. The assumption (A4), which is equivalent to $F Z (−x)=o( F ¯ Z (x))$, shows the r.v. Z’s left tails are lighter than the r.v. Y’s right tails. It is clear that all assumptions (A1)-(A4) are easily satisfied.

The main results of this paper are given below.

Theorem 2.1 Let the random variables${ X n ,n≥1}$introduced in Section  1 be WOD and, for some$r>1$, $E ( X n − ) r <∞$, $n≥1$. If the assumptions (A1)-(A4) hold and there exists a positive number$β< J F Z − −1$such that

$g L (n)=o ( n β ) and g U (n)=o ( n β ) ,$
(2.12)

then (1.1) and (1.2) hold, respectively.

Theorem 2.2 In addition to the conditions of Theorem  2.1, if one of the following two conditions is satisfied:

1. (I)

when$c≥0$, we have for arbitrarily fixed$ω>0$and some$r> J F Y +$

$E [ N ( t ) r 1 ( N ( t ) > ( 1 + ω ) λ ( t ) ) ] =O ( λ ( t ) ) ;$
(2.13)
2. (II)

when$c<0$, we have for all$0<ω<1$

$lim t → ∞ P r ( N ( t ) ≤ ( 1 − ω ) λ ( t ) ) F ¯ Y ( λ ( t ) ) =0,$
(2.14)

then (1.3) and (1.4) hold, respectively.

Remark 2.2 According to (3.13), (3.15), and (3.16), we can take

$M 1 =( C 1 / C 2 ) lim inf x → ∞ ( F ¯ Y ( u x / a ) / F ¯ Z ( x / b ) )$

and

$M 2 =( C 2 / C 1 ) lim sup x → ∞ ( F ¯ Z ( ν x / b ) / F ¯ Y ( x / a ) )$

in Theorem 2.1, respectively, where a, b, u, ν, $C 1$, and $C 2$ are some fixed positive constants. For the given distribution functions $F ¯ Z (x)$ and $F ¯ Y (x)$, we can obtain the sharp lower and upper bound $M 1$, $M 2$. Hence, though the above expressive forms are not nice-looking, causes no trouble for real applications. For $M ˜ 1$ and $M ˜ 2$, by the proof of Theorem 2.2, we can make a similar remark.

## 3 Proof of Theorem 2.1

We start with a series of lemmas based on which Theorem 2.1 will be proved. The proofs of the following Lemmas 3.1 and 3.2 are straightforward and are therefore omitted.

Lemma 3.1 If$E ( X + ) s <∞$for some$s>0$, then the relation

$lim n → ∞ sup x ≥ γ n n s F ¯ (x)=0$

holds for arbitrarily fixed$γ>0$.

Lemma 3.2 If$E ( X i ± ) q <∞$, $i≥1$, and$E ( Z ± ) q <∞$for some$q≥1$, and (2.8), (2.9) hold, then there exists positive constant$μ ˆ q ± <∞$such that

$∑ i = 1 n E ( X i ± ) q ≤n μ ˆ q ±$

holds for any$n=1,2,…$ .

Lemma 3.3 Let${ X n ,n≥1}$be a sequence of real-valued and WUOD r.v.s with$X n$’s d.f. $F n (x)=1− F ¯ n (x)$and$μ n =E X n =0$for every$n≥1$, and let${ c 1 , c 2 ,…}$be a sequence of real numbers satisfying$0, $i≥1$. If the assumptions (A1)-(A3) hold and there exists a positive number$β>0$such that

$g U (n)=O ( n β ) ,$
(3.1)

then there exists a constant $M 2 >0$ such that the relation

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n P r ( ∑ i = 1 n c i X i > x ) ∑ i = 1 n P r ( c i X i > x ) ≤ M 2$
(3.2)

holds for arbitrarily fixed constant$γ>0$, where$c ̲ n =( c 1 , c 2 ,…, c n )$.

Proof For arbitrarily fixed $0<ν<1$, let $X ˜ i =min{ X i ,νx/ c i }$, $i≥1$ and $S ˜ n = ∑ i = 1 n c i X ˜ i$. Using the standard truncation technique, we have

$P r ( ∑ i = 1 n c i X i > x ) ≤ ∑ i = 1 n P r ( c i X i >νx)+ P r ( S ˜ n >x).$
(3.3)

Now, we deal with the second term on the right-hand side of (3.3). Let $c=c(n,x, c ̲ n )=max{−log ∑ k = 1 n P r ( c k X k >νx),1}$, then we can obtain $lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n c=∞$ according to (2.8) and Lemma 3.1. Write $W= P r ( S ˜ n >x)/ ∑ i = 1 n P r ( c i X i >νx)$. For a positive number $h=h(n,x, c ̲ n )>0$, which we shall specify later, by Chebyshev’s inequality and Proposition 2.1, we have

$W ≤ g U ( n ) exp { − h x + c + ∑ i = 1 n log E e h c i X ˜ i } ≤ g U ( n ) exp { − h x + c + ∑ i = 1 n log [ ∫ − ∞ ν x / c i ( e h c i y − 1 ) d F i ( y ) + ( e h ν x − 1 ) P r ( c i X i > ν x ) + 1 ] } ≤ g U ( n ) exp { − h x + c + ∑ i = 1 n [ ∫ − ∞ ν x / c i ( e h c i y − 1 ) d F i ( y ) + ( e h ν x − 1 ) P r ( c i X i > ν x ) ] } ≤ g U ( n ) exp { − h x + c + ∑ i = 1 n ∫ − ∞ 0 ( e h c i y − 1 ) d F i ( y ) + ∑ i = 1 n ( ∫ 0 ν x c i c κ + ∫ ν x c i c κ ν x c i ) ( e h c i y − 1 ) d F i ( y ) + ( e h ν x − 1 ) ∑ i = 1 n P r ( c i X i > ν x ) } = g U ( n ) exp { − h x + c + I 1 + I 2 + I 3 + ( e h ν x − 1 ) ∑ i = 1 n P r ( c i X i > ν x ) } ,$
(3.4)

where $κ>1$ is an arbitrarily fixed constant. Take $h=(c−κ p 2 logc)/νx$, where $p 2 > J F Y +$. By (2.4) and (2.7),

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n h ≤ lim sup n → ∞ sup x ≥ γ n − log C 1 n F ¯ Y ( ν x / a ) ν x ≤ lim sup n → ∞ sup x ≥ γ n − log C 1 n ( ν x a ) − p 2 ν x = 0 .$

For $I 1$, we have

$I 1 h n = ∫ − ∞ 0 ( − 1 n ∑ i = 1 n F i ( y ) c i e h c i y ) d y ≤ b ( ∫ − ∞ − T + ∫ − T 0 ) 1 n ∑ i = 1 n F i ( y ) ( 1 − e h c i y ) d y − 1 n ∑ i = 1 n c i E X i − .$
(3.5)

Denote $g(n,h,y, c ̲ n )=( ∑ i = 1 n F i (y)(1− e h c i y ))/n$ and $g n (y)= sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n g(n,h,y, c ̲ n )$. By (2.9), we see that there exists $N>0$ such that for $n≥N$ and all $y≤−T$, $| g n (y)|≤ C 3 F Z (y)$. And for any $[s,t]⊂(−∞,−T]$, $| g n (y)|≤ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n (1− e b h s )→0$, $n→∞$ for all $y∈[s,t]$. Hence,

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n ∫ − ∞ − T g ( n , h , y , c ̲ n ) d y ≤ lim sup n → ∞ ∫ − ∞ − T g n ( y ) d y = ∫ − ∞ − T lim n → ∞ g n ( y ) d y = 0 .$
(3.6)

From the definition of $g n (y)$, we know that $| g n (y)|≤1$ for every n and all $y∈[−T,0)$, and $g n (y)→0$, $n→∞$ for all $y∈[−T,0)$. So,

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n ∫ − T 0 g ( n , h , y , c ̲ n ) d y ≤ lim sup n → ∞ ∫ − T 0 g n ( y ) d y = ∫ − T 0 lim n → ∞ g n ( y ) d y = 0 .$
(3.7)

Combining (3.6), (3.7) with (3.5), we obtain

$I 1 =φnh−h ∑ i = 1 n c i E X i − ,$
(3.8)

where $lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n φ=0$. For $I 2$ and $I 3$, we have

$I 2 + I 3 ≤ ∑ i = 1 n ( ∫ 0 ν x c i c κ h c i y e h c i y d F i ( y ) + ∫ ν x c i c κ ν x c i e h c i y d F i ( y ) ) ≤ ∑ i = 1 n ( h c i e h ν x c κ E X i + + e h ν x F ¯ i ( ν x c i c κ ) ) ,$
(3.9)

where $lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n x/ c κ →∞$ according to (2.4) and (2.7). Plugging (3.8) and (3.9) into (3.4) yields

$W ≤ g U ( n ) exp { − h x + c + φ h n + h b ∑ i = 1 n E X i + ( e h ν x c κ − 1 ) + C 2 n F ¯ Z ( ν x b c κ ) e h ν x + C 2 n F ¯ Z ( ν x b ) ( e h ν x − 1 ) } ≤ g U ( n ) exp { − h x + c + [ φ + b μ ˆ 1 + ( e h u ν / c κ − 1 ) ] h n + C 2 C ˜ 2 c κ p 2 n F ¯ Z ( ν x b ) e h ν x + C 2 n F ¯ Z ( ν x b ) e h ν x } ≤ g U ( n ) exp { − h x + c + [ φ + b μ ˆ 1 + ( e h u ν / c κ − 1 ) ] h n + B ˆ ( c κ p 2 + 1 ) n F ¯ Z ( ν x b ) e h ν x } ,$
(3.10)

where in the first step we apply (2.8), in the second step we use Lemma 3.2 and (2.2), and $B ˆ$ is an appropriately chosen positive number. By the value of h, we have

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n B ˆ ( c κ p 2 + 1 ) n F ¯ Z ( ν x b ) e h ν x <∞$

and

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n [ φ + b μ ˆ 1 + ( e h u ν / c κ − 1 ) ] h n + ( κ p 2 log c ) / ν c =0.$

Hence,

$W≤ g U (n) n − β exp { β log n + ( 1 − 1 ν ) c + o ( c ) + O ( 1 ) } .$
(3.11)

Using (2.3) and (2.8), we obtain

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n log n c ≤ 1 p 1 − 1 ,$

where $1< p 1 < J F Z −$. Taking $0<ν<( p 1 −1)/(β+ p 1 −1)<1$, from (3.11), we have

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n W ≤ lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n g U ( n ) n − β exp { ( β p 1 − 1 + 1 − 1 ν ) c + o ( c ) + O ( 1 ) } = 0 .$
(3.12)

Applying (2.7), (2.8), and (2.10), we know that there exists $M 2 >0$ such that

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n ∑ i = 1 n P r ( c i X i > ν x ) ∑ i = 1 n P r ( c i X i > x ) ≤ M 2 .$
(3.13)

Combining (3.12), (3.13) with (3.3), we can obtain (3.2). □

Lemma 3.4 Let${ X n ,n≥1}$be a sequence of real-valued and WOD r.v.s with$X n$’s d.f. $F n (x)=1− F ¯ n (x)$and$μ n =E X n =0$for every$n≥1$, and let${ c 1 , c 2 ,…}$be a sequence of real numbers satisfying$0, $i≥1$. If the assumptions (A1)-(A4) hold and there exists a positive number$β< J F Z − −1$such that

$g U (n)=o ( n β ) and g L (n)=o ( n β ) ,$
(3.14)

then there exists a constant $M 1 >0$ such that the relation

$lim inf n → ∞ inf x ≥ γ n inf c ̲ n ∈ [ a , b ] n P r ( ∑ i = 1 n c i X i > x ) ∑ i = 1 n P r ( c i X i > x ) ≥ M 1$
(3.15)

holds for arbitrarily fixed constant$γ>0$, where$c ̲ n =( c 1 , c 2 ,…, c n )$.

Proof It is sufficient to prove that

$lim inf n → ∞ inf x ≥ γ n inf c ̲ n ∈ [ a , b ] n P r ( ∑ i = 1 n c i X i > x ) ∑ i = 1 n P r ( c i X i > u x ) ≥1$
(3.16)

holds for arbitrarily fixed $u>1$. We write $A k ={ c k X k >ux}$ and $B k = ⋂ 1 ≤ i ≠ k ≤ n A i c$. Observing that $A k ∩ B k$, $k=1,2,…,n$, are mutually disjoint, we have

$P r ( ∑ i = 1 n c i X i > x ) ≥ ∑ k = 1 n [ P r ( A k ) − P r ( A k ∩ B k c ) − P r ( ∑ i = 1 n c i X i ≤ x , A k ∩ B k ) ] ≥ ∑ k = 1 n [ P r ( A k ) − ∑ 1 ≤ i ≠ k ≤ n P r ( A k ∩ A i ) − P r ( ∑ i : 1 ≤ i ≤ n , i ≠ k c i X i ≤ ( 1 − u ) x , A k ∩ B k ) ] ≥ ∑ k = 1 n P r ( A k ) [ 1 − g U ( n ) ∑ k = 1 n P r ( A k ) ] − ∑ k = 1 n P r ( ∑ i : 1 ≤ i ≤ n , i ≠ k c i X i ≤ ( 1 − u ) x , A k ∩ B k ) = J 1 − J 2 ,$
(3.17)

where at the third step we used Proposition 2.1.

For $J 1$, by (2.3), (2.8), and (3.14), we have for arbitrarily fixed $γ>0$

$lim inf n → ∞ inf x ≥ γ n inf c ̲ n ∈ [ a , b ] n J 1 ∑ k = 1 n P r ( c k X k > u x ) ≥ 1 − lim sup n → ∞ sup x ≥ γ n g U ( n ) n C 2 F ¯ Z ( u x b ) ≥ 1 − lim sup n → ∞ C 2 g U ( n ) n 1 − p 1 ( b u γ ) p 1 = 1 ,$
(3.18)

where $p 1 =β+1$.

Now we deal with $J 2$. For fixed $0, Let $W k =− X k$ and $W ˜ k =min{ W k ,(wx)/ c k }$, then

$J 2 ≤ ∑ k = 1 n P r ( A k ∩ B k , ⋃ i = 1 n { c i W i > w x } ) + ∑ k = 1 n P r ( ∑ i : 1 ≤ i ≤ n , i ≠ k c i X i ≤ ( 1 − u ) x , ⋂ j = 1 n { c j W j ≤ w x } ) ≤ ∑ i = 1 n P r ( c i W i > w x ) + ∑ k = 1 n P r ( c k W ˜ k ≥ ( u − 1 ) x ) = K 1 + K 2 .$
(3.19)

For $K 1$, by (2.7), (2.9)-(2.11), we have

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n K 1 ∑ i = 1 n P r ( c i X i > u x ) ≤ lim sup x → ∞ C 3 F Z ( − w b x ) C 1 F ¯ Y ( u a x ) =0.$
(3.20)

For $K 2$, using Chebyshev’s inequality and Proposition 2.1 again, we have

$K 2 ≤ ∑ k = 1 n g L ( n − 1 ) exp { − h ( u − 1 ) x + ∑ i : 1 ≤ i ≤ n , i ≠ k log E e h c i W ˜ i } ≤ ∑ k = 1 n g L ( n − 1 ) exp { − h ( u − 1 ) x + ∑ i : 1 ≤ i ≤ n , i ≠ k [ ∫ − ∞ w x c i ( e h c i y − 1 ) d F W i ( y ) + ( e h w x − 1 ) P r ( c i W i > w x ) ] } ≤ ∑ k = 1 n g L ( n − 1 ) exp { − h ( u − 1 ) x + ∑ i : 1 ≤ i ≤ n , i ≠ k [ ∫ − ∞ 0 ( e h c i y − 1 ) d F W i ( y ) + ∫ 0 w x c i e h c i y − 1 − h c i y ( c i y ) s ( c i y ) s d F W i ( y ) + h c i E X i − + ( e h w x − 1 ) P r ( c i W i > w x ) ] } ,$
(3.21)

where $h=(log( w s − 1 x s /n μ ˆ s − +1))/wx$ and $s>1$. Using similar techniques as in (3.8), we can obtain

$| ∑ i : 1 ≤ i ≤ n , i ≠ k [ ∫ − ∞ 0 ( e h c i y − 1 ) d F W i ( y ) + h c i E X i − ] | ≤|α|nh,$
(3.22)

where $α→0$ holds uniformly for $x≥γn$, as $n→∞$. By (2.9) and (2.11),

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n ∑ i : 1 ≤ i ≤ n , i ≠ k ( e h w x − 1 ) P r ( c i W i > w x ) ≤ lim sup x → ∞ w s − 1 μ ˆ s − C 3 x s F ¯ Y ( b w x ) → 0 .$
(3.23)

Take sufficiently large n such that $|α|≤(u−1)γ/2$. Combining (3.21)-(3.23) and observing the monotonicity of $0≤( e h c i y −1−h c i y)/ ( c i y ) s$ for all $y>0$, we have

$K 2 ≤ ∑ k = 1 n g L ( n − 1 ) n − β exp { β log n − h ( u − 1 ) x + | α | n h + e h w x − 1 − h w x ( w x ) s ∑ i : 1 ≤ i ≤ n , i ≠ k c i s E ( X i − ) s + o ( 1 ) } ≤ ∑ k = 1 n g L ( n − 1 ) n − β exp { log ( x γ ) β + log ( w s − 1 x s n μ ˆ s − + 1 ) − u − 1 2 w + e h w x − 1 ( w x ) s b s n μ ˆ s − + o ( 1 ) } ≤ C ˜ n x β − ( s − 1 ) ( u − 1 ) 2 w ,$
(3.24)

where $C ˜$ is some positive constant. For fixed $u>1$, we take $0 such that $( s − 1 ) ( u − 1 ) 2 w >β+ J F Y +$. By (2.4) and (2.7), we have

$lim sup n → ∞ sup x ≥ γ n sup c ̲ n ∈ [ a , b ] n K 2 ∑ k = 1 n P r ( c k X k > u x ) ≤ lim sup x → ∞ C ˜ x β − ( s − 1 ) ( u − 1 ) 2 w C 1 F ¯ Y ( u a x ) =0.$
(3.25)

Combing (3.17)-(3.20) with (3.25), we can obtain (3.16). This ends the proof of Lemma 3.4. □

Proof of Theorem 2.1 By Lemma 3.3, for arbitrarily fixed $γ>0$, we have uniformly for $x≥γn$

$P r ( ∑ k = 1 n θ k X k > x ) = E [ P r ( ∑ k = 1 n θ k X k > x | θ 1 , θ 2 , … , θ n ) ] ≲ M 2 E [ ∑ k = 1 n P r ( θ k X k > x | θ 1 , θ 2 , … , θ n ) ] = M 2 ∑ k = 1 n P r ( θ k X k > x ) .$
(3.26)

According to Lemma 3.4 and using a similar method of proof as in (3.26), we can obtain the remainder of Theorem 2.1. □

## 4 Proof of Theorem 2.2

For proving Theorems 2.2, we first give two lemmas.

Lemma 4.1 Let${ X n ,n≥1}$be a sequence of real-valued and WUOD r.v.s with$X n$’s d.f. $F n (x)=1− F ¯ n (x)$and$0for every$n≥1$, and Let${ θ i ,i≥1}$be a sequence of non-negative r.v.s satisfying$P r (a≤ θ i ≤b)=1$, $i≥1$, $0and independent of${ X n ,n≥1}$. If (2.8) and$E Z + <∞$hold and$g U (n)=O( n β )$for some positive number β, then for every fixed$u>0$, there is$D ˆ = D ˆ (u)>0$such that

$P r ( ∑ i = 1 n θ i X i > x ) ≤ ∑ i = 1 n P r ( θ i X i >ux)+ D ˆ ( n x ) 1 u n β$
(4.1)

holds for large n and all$x>0$.

Proof Using the techniques similar to Lemma 3.3 with some obvious modifications, we can prove the lemma. □

Combining Lemma 2.1 of Chen et al. with Lemma 3.1 of Ng et al., we can obtain the following lemma.

Lemma 4.2 If a non-negative random process${ζ(t),t≥0}$satisfies$Eζ(t)→1$, $t→∞$, then (i)-(iv) are mutually equivalent:

1. (i)

$ζ(t) → P r 1$, as$t→∞$;

2. (ii)

for every fixed$θ>0$, $Eζ(t) 1 { ζ ( t ) − 1 > θ } =o(1)$;

3. (iii)

for every fixed$θ>0$, $Eζ(t) 1 { | ζ ( t ) − 1 | > θ } =o(1)$;

4. (iv)

for every fixed$0<θ<1$, $P r (1−ζ(t)≥θ)=o(1)$.

By Lemma 4.2 and (2.13), we know that

$N ( t ) λ ( t ) → P r 1.$
(4.2)

Proof of Theorem 2.2 Now, we prove Theorem 2.2 under condition (I). Using Theorem 2.1 and (2.8), we obtain for any fixed $σ>0$ the result that there exists a positive integral number N such that when $n≥N$, for sufficiently large x,

$P r ( ∑ i = 1 n θ i X i > x ) ≤( M 2 +σ) ∑ i = 1 n P r ( θ i X i >x)≤( M 2 +σ) C 2 n F ¯ Z ( x b ) .$
(4.3)

It is clear that for every $n=1,2,…,N$ and all large x,

$P r ( ∑ i = 1 n θ i X i > x ) ≤ ∑ i = 1 n P r ( θ i X i >x/N)≤ C 2 n F ¯ Z ( x N b ) .$
(4.4)

Hence, by (4.3) and (4.4), there exists some positive number D, for every $n=1,2,…$ , and all sufficiently large x,

$P r ( ∑ i = 1 n θ i X i > x ) ≤Dn F ¯ Z (x).$
(4.5)

Take $0<ω<1$ such that $c(1+ω)<γ$. Throughout this proof, we suppose that $x∈[γλ(t),∞)$. Consider the following decomposition:

$P r ( S c θ ( t ) > x ) = ( ∑ n < ( 1 − ω ) λ ( t ) + ∑ ( 1 − ω ) λ ( t ) ≤ n ≤ ( 1 + ω ) λ ( t ) + ∑ n > ( 1 + ω ) λ ( t ) ) P r ( S n θ > x − n c ) P r ( N ( t ) = n ) = L 1 + L 2 + L 3 .$
(4.6)

Firstly, we deal with $L 1$. For sufficiently large t, by (4.5), we have

$L 1 ≤ ∑ n < ( 1 − ω ) λ ( t ) P r ( S n θ > x − ( 1 − ω ) c λ ( t ) ) P r ( N ( t ) = n ) ≤ D F ¯ Z ( x − ( 1 − ω ) c λ ( t ) ) ∑ n < ( 1 − ω ) λ ( t ) n P r ( N ( t ) = n ) .$

For convenience, write $H=E[ ∑ i = 1 N ( t ) P r ( θ i X i >x−cλ(t))]$. According to $x−(1−ω)cλ(t)≍x−cλ(t)$, (2.7), (2.10), and (iv) of Lemma 4.2, we have

$lim sup t → ∞ sup x ≥ γ λ ( t ) L 1 H ≤ lim sup t → ∞ sup x ≥ γ λ ( t ) D F ¯ Z ( x − ( 1 − ω ) c λ ( t ) ) ∑ n < ( 1 − ω ) λ ( t ) n P r ( N ( t ) = n ) C 1 F ¯ Y ( x − c λ ( t ) a ) E [ N ( t ) 1 { N ( t ) > n 0 } ] ≤ D ˜ lim sup t → ∞ ∑ n < ( 1 − ω ) λ ( t ) n P r ( N ( t ) = n ) E N ( t ) − n 0 ≤ D ˜ lim sup t → ∞ E [ N ( t ) λ ( t ) 1 { N ( t ) < ( 1 − ω ) λ ( t ) } ] 1 − n 0 λ ( t ) ≤ D ˜ ( 1 − ω ) lim t → ∞ P r ( N ( t ) λ ( t ) < 1 − ω ) = 0 ,$
(4.7)

where $D ˜$ is some positive constant.

Secondly, we deal with $L 2$. On the one hand, by Theorem 2.1, for arbitrary $ε 1 >0$ and sufficiently large t,

$L 2 ≥ ( M 1 − ε 1 ) ∑ ( 1 − ω ) λ ( t ) ≤ n ≤ ( 1 + ω ) λ ( t ) ∑ i = 1 n P r ( θ i X i > x − n c ) P r ( N ( t ) = n ) ≥ ( M 1 − ε 1 ) C 1 F ¯ Y ( x − ( 1 − ω ) c λ ( t ) a ) ∑ ( 1 − ω ) λ ( t ) ≤ n ≤ ( 1 + ω ) λ ( t ) n P r ( N ( t ) = n ) .$
(4.8)

By (2.8), we have $H≤ C 2 F ¯ Z ((x−cλ(t))/b)λ(t)$. Using (2.10) and (iii) of Lemma 4.2, we know that there is a positive constant $M ˜ 1$ such that

$lim inf t → ∞ inf x ≥ γ λ ( t ) L 2 H ≥ M ˜ 1 lim t → ∞ E [ N ( t ) λ ( t ) 1 { | N ( t ) λ ( t ) − 1 | ≤ ω } ] = M ˜ 1 .$
(4.9)

On the other hand, using similar techniques as in (4.8), for any $ε 2 >0$ and sufficiently large t, we have

$L 2 ≤( M 2 + ε 2 ) C 2 F ¯ Z ( x − ( 1 + ω ) c λ ( t ) b ) ∑ ( 1 − ω ) λ ( t ) ≤ n ≤ ( 1 + ω ) λ ( t ) n P r ( N ( t ) = n ) .$
(4.10)

By (2.7), we have

$H≥ C 1 F ¯ Y ( x − c λ ( t ) a ) E [ N ( t ) 1 { N ( t ) > n 0 } ] .$
(4.11)

Then, by (4.10) and (4.11), there exists a positive number $M ˜ 2$ such that

$lim sup t → ∞ sup x ≥ γ λ ( t ) L 2 H ≤ M ˜ 2 lim t → ∞ E [ N ( t ) λ ( t ) 1 { | N ( t ) λ ( t ) − 1 | ≤ ω } ] 1 − n 0 λ ( t ) = M ˜ 2 .$
(4.12)

Finally, we deal with $L 3$. Taking $0<υ<1$ and splitting $L 3$ into two parts, we obtain

$L 3 = ( ∑ ( 1 + ω ) λ ( t ) < n ≤ ( 1 − υ ) x / c + ∑ n > max { ( 1 + ω ) λ ( t ) , ( 1 − υ ) x / c } ) P r ( ∑ i = 1 n θ i X i > x − n c ) P r ( N ( t ) = n ) = R 1 + R 2 ,$
(4.13)

where $R 1$ is understood as 0 in case $(1+ω)λ(t)>(1−υ)x/c$. For $R 1$, taking $u=1/p$ in (4.1) and letting $p> J F Y +$, we have

$R 1 ≤ ∑ ( 1 + ω ) λ ( t ) < n ≤ ( 1 − υ ) x / c P r ( ∑ i = 1 n θ i X i > υ x ) P r ( N ( t ) = n ) ≤ ∑ ( 1 + ω ) λ ( t ) < n ≤ ( 1 − υ ) x / c ( ∑ i = 1 n P r ( θ i X i > υ x / p ) + D ˆ ( υ x ) − p n p + β ) P r ( N ( t ) = n ) ≤ C 2 F ¯ Z ( υ x b p ) E [ N ( t ) 1 { N ( t ) > ( 1 + ω ) λ ( t ) } ] + D ˆ ( υ x ) − p E [ N ( t ) p + β 1 { N ( t ) > ( 1 + ω ) λ ( t ) } ] .$
(4.14)

Hence, according to (ii) of Lemma 4.2, (2.13), and (2.4), we have

$lim sup t → ∞ sup x ≥ γ λ ( t ) R 1 H ≤ lim sup t → ∞ sup x ≥ γ λ ( t ) C 2 F ¯ Z ( υ x b p ) E [ N ( t ) λ ( t ) 1 { N ( t ) > ( 1 + ω ) λ ( t ) } ] C 1 F ¯ Y ( x − c λ ( t ) a ) ( 1 − n 0 λ ( t ) ) + lim sup t → ∞ sup x ≥ γ λ ( t ) D ˆ ( υ x ) − p C 1 F ¯ Y ( x − c λ ( t ) a ) × lim sup t → ∞ sup x ≥ γ λ ( t ) E [ N ( t ) p + β 1 { N ( t ) > ( 1 + ω ) λ ( t ) } ] / λ ( t ) ( 1 − n 0 λ ( t ) ) = 0 .$
(4.15)

For $R 2$, we have

$lim sup t → ∞ sup x ≥ γ λ ( t ) R 2 H ≤ lim sup t → ∞ sup x ≥ γ λ ( t ) ∑ n > max { ( 1 + ω ) λ ( t ) , ( 1 − υ ) x / c } n p ( ( 1 − υ ) x / c ) p P r ( N ( t ) = n ) C 1 F ¯ Y ( x − c λ ( t ) a ) E [ N ( t ) 1 { N ( t ) > n 0 } ] ≤ lim sup t → ∞ sup x ≥ γ λ ( t ) ( ( 1 − υ ) x / c ) − p E [ N ( t ) p 1 { N ( t ) > ( 1 + ω ) λ ( t ) } ] / λ ( t ) C 1 F ¯ Y ( x − c λ ( t ) a ) ( 1 − n 0 λ ( t ) ) = 0 .$
(4.16)

Combing (4.6), (4.7), (4.9), (4.12), (4.13), and (4.15) with (4.16), we finish the proof under condition (I).

Finally, we prove Theorem 2.2 under condition (II). Without loss of generality, we assume $c<γ<0$. We still take $0<ω<1$ such that $c(1+ω)<γ<0$ and use the decomposition (4.6). For $L 1$, we take $γ 1 >0$ and divide the interval $[γλ(t),∞)$ into two parts, which are $[γλ(t), γ 1 λ(t))$ and $[ γ 1 λ(t),∞)$. When $x∈[ γ 1 λ(t),∞)$, we have

$F ¯ Z ( x − c λ ( t ) ) ≥ F ¯ Z ( ( 1 − c / γ 1 ) x ) ≍ F ¯ Z (x).$
(4.17)

When $x∈[γλ(t), γ 1 λ(t))$, we have

$F ¯ Y ( x − c λ ( t ) ) ≥ F ¯ Y ( ( γ 1 − c ) λ ( t ) ) ≍ F ¯ Y ( λ ( t ) ) .$
(4.18)

Applying (2.14), (4.5), (4.17), and (4.18), we obtain

$lim sup t → ∞ sup x ≥ γ λ ( t ) L 1 H ≤ lim sup t → ∞ sup x ≥ γ 1 λ ( t ) D ( 1 − ω ) F ¯ Z ( x ) P r ( N ( t ) ≤ ( 1 − ω ) λ ( t ) ) C 1 F ¯ Y ( x − c λ ( t ) a ) ( 1 − n 0 λ ( t ) ) + lim sup t → ∞ sup γ λ ( t ) ≤ x < γ 1 λ ( t ) D ( 1 − ω ) P r ( N ( t ) ≤ ( 1 − ω ) λ ( t ) ) C 1 F ¯ Y ( x − c λ ( t ) a ) ( 1 − n 0 λ ( t ) ) = 0 .$
(4.19)

For $L 3$, since $x−cn≥γλ(t)−cn≥(γ ( 1 + ω ) − 1 −c)n$, then according to Theorem 2.1, (2.10), and Lemma 4.2, we have

$lim sup t → ∞ sup x ≥ γ λ ( t ) L 3 H ≤ lim sup t → ∞ sup x ≥ γ λ ( t ) M 2 ∑ n > ( 1 + ω ) λ ( t ) ∑ i = 1 n P r ( θ i X i > x − c n ) P r ( N ( t ) = n ) C 1 F ¯ Y ( x − c λ ( t ) a ) E [ N ( t ) 1 { N ( t ) > n 0 } ] ≤ lim sup t → ∞ sup x ≥ γ λ ( t ) M 2 C 2 F ¯ Z ( x − c λ ( t ) b ) E [ N ( t ) λ ( t ) 1 { N ( t ) > ( 1 + ω ) λ ( t ) } ] C 1 F ¯ Y ( x − c λ ( t ) a ) ( 1 − n 0 λ ( t ) ) = 0 .$
(4.20)

For $L 2$, observing $λ(t)≤ ( γ − c ) − 1 (x−cλ(t))$ and $c<0$, by Theorem 2.1, (2.14), and (iii) of Lemma 4.2, we know that, on the one hand, there exists a positive number $M ˜ 1$ such that

$lim inf t → ∞ inf x ≥ γ λ ( t ) L 2 H ≥ lim inf t → ∞ inf x ≥ γ λ ( t ) M 1 ∑ ( 1 − ω ) λ ( t ) ≤ n ≤ ( 1 + ω ) λ ( t ) ∑ i = 1 n P r ( θ i X i > x − c n ) P r ( N ( t ) = n ) C 2 F ¯ Z ( x − c λ ( t ) b ) λ ( t ) ≥ lim inf t → ∞ inf x ≥ γ λ ( t ) M 1 C 1 F ¯ Y ( x − c ( 1 + ω ) λ ( t ) a ) E [ N ( t ) λ ( t ) 1 { | N ( t ) λ ( t ) − 1 | ≤ ω } ] C 2 F ¯ Z ( x − c λ ( t ) b ) ≥ lim inf t → ∞ inf x ≥ γ λ ( t ) M 1 C 1 F ¯ Y ( a − 1 ( 1 − c ω ( γ − c ) − 1 ) ( x − c λ ( t ) ) ) E [ N ( t ) λ ( t ) 1 { | N ( t ) λ ( t ) − 1 | ≤ ω } ] C 2 F ¯ Z ( x − c λ ( t ) b ) ≥ M ˜ 1 ;$
(4.21)

on the other hand, there exists a positive number $M ˜ 2$ such that

$lim sup t → ∞ sup x ≥ γ λ ( t ) L 2 H ≤ lim sup t → ∞ sup x ≥ γ λ ( t ) M 2 C 2 F ¯ Z ( b − 1 ( 1 + c ω ( γ − c ) − 1 ) ( x − c λ ( t ) ) ) E [ N ( t ) λ ( t ) 1 { | N ( t ) λ ( t ) − 1 | ≤ ω } ] C 1 F ¯ Y ( x − c λ ( t ) a ) ( 1 − n 0 λ ( t ) ) ≤ M ˜ 2 .$
(4.22)

Combing (4.19)-(4.22), we finish the proof under condition (II). □

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## Acknowledgements

The authors would like to thank the two referees for careful reading of our manuscript and for helpful and valuable comments and suggestions, which helped us improve the earlier version of the paper. The research of the authors was supported by the Natural Science Foundation of the Inner Mongolia Autonomous Region (No. 2013MS0101), the National Natural Sciences Foundation of China (No. 11201317), and the Beijing Municipal Education Commission Foundation (No. KM201210028005).

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Bai, X., Song, L. & Hu, T. Large deviations for randomly weighted sums with dominantly varying tails and widely orthant dependent structure. J Inequal Appl 2014, 140 (2014). https://doi.org/10.1186/1029-242X-2014-140 