R如何在应用条件的情况下进行简单的向量/矩阵计算？

我有一个向量，即。 更改向量（其中日期为行名）

和一个矩阵：

    2012-07-30  2012-08-06  2012-08-13  2012-08-20
2012-05-28  1.0 2.0 3.0 2.0
2012-06-04  1.0 2.0 3.0 2.0
2012-06-11  1.0 2.0 3.0 2.0
2012-06-18  1.0 2.0 3.0 2.0
2012-06-25  1.0 2.0 3.0 2.0
2012-07-02  1.0 2.0 3.0 2.0
2012-07-09  1.0 2.0 3.0 2.0
2012-07-16  1.0 2.0 3.0 2.0
2012-07-23  1.0 2.0 3.0 2.0
2012-07-30  1.0 2.0 3.0 2.0
2012-08-06  NA  2.0 3.0 2.0
2012-08-13  NA  NA  3.0 2.0
2012-08-20  NA  NA  NA  2.0
2012-08-27  NA  NA  NA  NA

我想做一个简单的计算，如果我用矩阵乘以向量 那么2012-08-13的所有栏目将增加150% i、 e.至4.5。。看这个例子，我在那里做了计算

t(t(my_matrix) * (change_vector)) 

    2012-07-30  2012-08-06  2012-08-13  2012-08-20
2012-05-28  1.0 2.0 4.5 2.0
2012-06-04  1.0 2.0 4.5 2.0
2012-06-11  1.0 2.0 4.5 2.0
2012-06-18  1.0 2.0 4.5 2.0
2012-06-25  1.0 2.0 4.5 2.0
2012-07-02  1.0 2.0 4.5 2.0
2012-07-09  1.0 2.0 4.5 2.0
2012-07-16  1.0 2.0 4.5 2.0
2012-07-23  1.0 2.0 4.5 2.0
2012-07-30  1.0 2.0 4.5 2.0
2012-08-06  NA  2.0 4.5 2.0
2012-08-13  NA  NA  4.5 2.0
2012-08-20  NA  NA  NA  2.0
2012-08-27  NA  NA  NA  NA

然而，我想限制乘法，使其仅计算相对于该日期的最后9周，例如，对于相对于提升日期的9周，列2012-08-13仅增加到4.5 i、 e.输出应为：

    2012-07-30  2012-08-06  2012-08-13  2012-08-20
2012-05-28  1.0 2.0 3.0 2.0
2012-06-04  1.0 2.0 3.0 2.0
2012-06-11  1.0 2.0 4.5 2.0
2012-06-18  1.0 2.0 4.5 2.0
2012-06-25  1.0 2.0 4.5 2.0
2012-07-02  1.0 2.0 4.5 2.0
2012-07-09  1.0 2.0 4.5 2.0
2012-07-16  1.0 2.0 4.5 2.0
2012-07-23  1.0 2.0 4.5 2.0
2012-07-30  1.0 2.0 4.5 2.0
2012-08-06  NA  2.0 4.5 2.0
2012-08-13  NA  NA  4.5 2.0
2012-08-20  NA  NA  NA  2.0
2012-08-27  NA  NA  NA  NA

请注意，在我的实际例子中，我的矩阵相当大，变化向量将有很多不同的值

---

谢谢

以后，如果您使用类似于

dput（）

的方法发布代码以读取数据，这会很有帮助。让那些愿意提供帮助的人更容易接受

change_vector <- structure(c(1, 1, 1.5, 1), 
    .Names = c("2012-07-30", "2012-08-06", "2012-08-13", "2012-08-20"))
my_matrix <- structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, NA, NA, NA, 2, 
    2, 2, 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, 3, 3, 3, 3, 3, 3, 3, 
    3, 3, 3, 3, 3, NA, NA, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
    NA), .Dim = c(14L, 4L), .Dimnames = list(c("2012-05-28", "2012-06-04", 
    "2012-06-11", "2012-06-18", "2012-06-25", "2012-07-02", "2012-07-09", 
    "2012-07-16", "2012-07-23", "2012-07-30", "2012-08-06", "2012-08-13", 
    "2012-08-20", "2012-08-27"), c("2012-07-30", "2012-08-06", "2012-08-13", 
    "2012-08-20")))

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我不确定您是否只想删除9周以上的内容（这是我编写代码的目的），或者您是否还需要在将来删除内容（您必须修改代码才能这样做）。像这样的。。。您需要的不是

difweeks>=-9

而是类似于

difweeks>=-9&difweeks的内容，请更清楚地说明这一点。目前还不清楚你在问什么。请添加可复制的数据。我添加了更多的细节，这是否有助于您需要告诉我们，我们是否可以依靠NA的良好结构，如上图所示。
change_vector <- structure(c(1, 1, 1.5, 1), 
    .Names = c("2012-07-30", "2012-08-06", "2012-08-13", "2012-08-20"))
my_matrix <- structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, NA, NA, NA, 2, 
    2, 2, 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, 3, 3, 3, 3, 3, 3, 3, 
    3, 3, 3, 3, 3, NA, NA, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
    NA), .Dim = c(14L, 4L), .Dimnames = list(c("2012-05-28", "2012-06-04", 
    "2012-06-11", "2012-06-18", "2012-06-25", "2012-07-02", "2012-07-09", 
    "2012-07-16", "2012-07-23", "2012-07-30", "2012-08-06", "2012-08-13", 
    "2012-08-20", "2012-08-27"), c("2012-07-30", "2012-08-06", "2012-08-13", 
    "2012-08-20")))

# calculate the difference in weeks between the matrix and vector dates
mdates <- as.Date(dimnames(my_matrix)[[1]])
vdates <- as.Date(names(change_vector))
difweeks <- outer(mdates, vdates, "-") / 7

# define a matrix that is 1 when the adjustment should be made, and 0 otherwise
adjonlyif <- 1*(difweeks >= -9)

# subtract 1 from the change vector
cv2 <- change_vector - 1

# multiply the adjusted change vector by the adjustment matrix, add 1, and multiply by the original matrix
my_matrix * (1 + t(t(adjonlyif) * cv2))

my_matrix * (1 + t(t(difweeks >= -9) * (change_vector - 1)))