我想适合一个发行版。 如果我有一个数据集,我可以很容易做到:
library("fitdistrplus")
data_raw <- c(1018259, 1191258, 1265953, 1278234, 1630327, 1780896, 1831466, 1850446, 1859801, 1928695, 2839345, 2918672, 3058274, 3303089, 3392047, 3581341, 4189346, 5966833, 11451508)
fitdist(data_raw, "lnorm")
这就是我要使对数正态分布适合数据集的方式。
但是,如果我没有一个数据集,只是平均值,标准差和一些分位数,该怎么办?例如:
平均值:2965042
std.dev:2338555
分位数:
0.1:1251014
0.5:1928695
0.8:3467765
0.9:4544843
0.95:6515300
0.999:11352784
您将如何继续对此类数据进行估算?
感谢您和最诚挚的问候
诺比
答案 0 :(得分:1)
只需使用at Renci.SshNet.Sftp.SftpSession.RequestRead(Byte[] handle, UInt64 offset, UInt32 length)
at Renci.SshNet.Sftp.SftpFileStream.Read(Byte[] buffer, Int32 offset, Int32 count)
at System.IO.Compression.ZipHelper.ReadBytes(Stream stream, Byte[] buffer, Int32 bytesToRead)
at System.IO.Compression.ZipHelper.SeekBackwardsAndRead(Stream stream, Byte[] buffer, Int32& bufferPointer)
at System.IO.Compression.ZipHelper.SeekBackwardsToSignature(Stream stream, UInt32 signatureToFind)
at System.IO.Compression.ZipArchive.ReadEndOfCentralDirectory()
at System.IO.Compression.ZipArchive.Init(Stream stream, ZipArchiveMode mode, Boolean leaveOpen)
at System.IO.Compression.ZipArchive..ctor(Stream stream, ZipArchiveMode mode, Boolean leaveOpen, Encoding entryNameEncoding)
at ExcelDataReader.Core.ZipWorker..ctor(Stream fileStream)
at ExcelDataReader.ExcelOpenXmlReader..ctor(Stream stream)
at ExcelDataReader.ExcelReaderFactory.CreateOpenXmlReader(Stream fileStream, ExcelReaderConfiguration configuration)
拟合模型:
nls