交易者替代成本 [英] Traminer substitution cost

问题描述

我对过渡成本矩阵存在逻辑上的问题.我正在使用R包Traminer处理序列差异.

I have a logical problem with the transition cost matrix. I am working on sequences dissimilarity using the R package Traminer.

我尝试给你一个简单的例子(非常简单，但是希望对我的问题有所帮助):

I try to give you a simple example (very simple, but I hope useful to explain my problem):

有3个序列，我想计算不相似矩阵. 字母是:H(健康)，I(在家中)，IH(在医院中)，D(去世)

There are three sequences and I want to be calculate the dissimilarity matrix. The alphabet is: H (in health), I (ill at home), IH (ill at hospital), D (died)

我观察了3个受试者的5个观察结果.这些是顺序:

I observe the 3 subjects for 5 observations. These are the sequences:

H – H – I – D – D 
H – I – I – I – D 
I – I – H – IH – IH 

替代成本矩阵是一个4x4的表格(状态x状态). 它必须对称吗? 这是我的逻辑问题:尽管有可能从状态H，I或IH过渡"到状态Died，但相反是不合逻辑的.

The substitution cost matrix is a 4x4 table (state x state). It must be symmetric? This is my logical problem: while it is possible to "transit" from states H, I or IH to state Died, the contrary is illogical.

我可以在TraMineR中使用非对称替代成本矩阵吗?

Can I use a non-symmetric substitution cost matrix in TraMineR?

如果在我的数据库中，从状态"I"到"D"的替换成本(例如，用sm = "TRATE"计算)比从状态"I"到"IH"的替换成本低(0.5)( 0.6)，则OM算法将"I"替换为"D"，而不是"HI".

If, in my database, the substitution cost (calculated with sm = "TRATE", for instance) from state "I" to "D" is lower (0.5) than the substitution cost from state 'I' to 'IH' (0.6) , the OM algorithm substitute the "I" whith "D" instead of "HI".

推荐答案

在我看来，您正在寻找自定义费用矩阵.不必使用TRATE或CONSTANT方法.

it seems to me that you're looking for a custom cost matrix. It is not mandatory to use either the TRATE or CONSTANT method.

要创建自定义矩阵，您只需执行以下操作即可:

To create a custom matrix you'll just have to do something like this:

myscm <- matrix(c(0,1,2, 
                  1,0,2, 
                  2,2,0), nrow=3, ncol=3) 
dist.om <- seqdist(my.seq, method="OM", sm=myscm)

其中myscm是您的自定义矩阵

此内容取自 http ://lists.r-forge.r-project.org/pipermail/traminer-users/2011-July/000075.html

我相信您有两种选择:

1)为所有过渡创建理由并创建完整的自定义矩阵

1) Create a rationale for all the transitions and a full custom matrix

2)获取已经生成的转换矩阵(使用seqsubm(your.seq, method = "TRATE"))，仅更改不一致的值.这就是我在上次分析中所做的.

2) Get the transition matrix you've already generated (using seqsubm(your.seq, method = "TRATE") ) and change just the inconsistent values. That's what I've done in my last analysis.

但请记住，吉尔伯特(Gilbert)在成对距离矩阵

But keep in mind the point made by Gilbert in An "asymmetric" pairwise distance matrix

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