在R语言中按球队分组计算加权滚动平均值的方案求助

我有一个名为games_h的DataFrame，仅展示了部分数据，实际包含多支球队信息，且已按日期、球队、比赛编号排序。希望按Team字段分组，对指定列计算加权滚动平均值——规则是最近一场比赛权重高于前一场（比如权重比2:1，计算公式为(Game_1*1 + Game_2*2)/3）。

数据结构 #

games_h的结构如下：

dput(games_h)
structure(list(GameId = c(16, 16, 37, 37, 57, 57), GameDate = structure(c(17905, 
17905, 17916, 17916, 17926, 17926), class = "Date"), NeutralSite = c(0, 
0, 0, 0, 0, 0), AwayTeam = c("Virginia Cavaliers", "Virginia Cavaliers", 
"Florida State Seminoles", "Florida State Seminoles", "Syracuse Orange", 
"Syracuse Orange"), HomeTeam = c("Boston College Eagles", "Boston College Eagles", 
"Boston College Eagles", "Boston College Eagles", "Boston College Eagles", 
"Boston College Eagles"), Team = c("Virginia Cavaliers", "Boston College Eagles", 
"Florida State Seminoles", "Boston College Eagles", "Syracuse Orange", 
"Boston College Eagles"), Home = c(0, 1, 0, 1, 0, 1), Score = c(83, 
56, 82, 87, 77, 71), AST = c(17, 6, 12, 16, 11, 13), TOV = c(10, 
8, 9, 13, 11, 11), STL = c(5, 4, 4, 6, 6, 5), BLK = c(6, 0, 4, 
4, 1, 0), Rebounds = c(38, 18, 36, 33, 23, 23), ORB = c(7, 4, 
16, 10, 7, 6), DRB = c(31, 14, 20, 23, 16, 17), FGA = c(55, 57, 
67, 55, 52, 45), FGM = c(33, 22, 28, 27, 29, 21), X3FGM = c(8, 
7, 8, 13, 11, 9), X3FGA = c(19, 25, 25, 21, 26, 22), FTA = c(14, 
9, 24, 28, 15, 23), FTM = c(9, 5, 18, 20, 8, 20), Fouls = c(16, 
12, 25, 20, 19, 19), Game_Number = 1:6, Count = c(1, 1, 1, 1, 
1, 1)), class = c("grouped_df", "tbl_df", "tbl", "data.frame"
), row.names = c(NA, -6L), groups = structure(list(HomeTeam = "Boston College Eagles", 
    .rows = structure(list(1:6), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -1L), .drop = TRUE))

预期输出 #

以Score列为例，预期输出如下：

尝试代码 #

我自己编写了加权平均计算函数，但无法批量应用到分组后的指定列中，尝试的代码如下：

weighted_avg<-function(x, wt1, wt2) {
  
rs1 = rollsum(x,1,align = "right")
rs2 = rollsum(x,2,align = "right")
rs1=rs1[-1]
rs3 = rs2 - rs1
weighted_avg= ((rs3 * wt2)+ (rs1*wt1))/(wt1+wt2)
return(weighted_avg)
}

weighted_avg(csum$Score_Y, 2, 1)
apply(csum$Score_Y , 2, weighted_avg, wt1 = 2, wt2=1)
test<-csum %>%
  group_by(Team)%>%
  group_map(across(c(Score:Fouls), weighted_avg(.x$Team, 2, 1)  ))

test<-csum %>%
  group_by(Team)%>%
  group_walk(across(c(Score:Fouls),weighted_avg(.~,2,1)  ))

需求 #

请给出解决方案：如何在R中按Team分组，将上述加权平均函数批量应用到Score至Fouls的列中。

内容的提问来源于stack exchange，提问作者d3hero23