Analisis Regresi Robust Estimasi Least Trimmed Square dan Estimasi Maximum Likelihood pada Pemodelan IPM di Pulau Sulawesi

Analisis dan Sintesis Sinyal Suara

Audio signal information with high quality would help the television audience to increase the perception of the information displayed. Transmission channel capacity will become limited, while the need of channel communication is increased. The research aim is coding the audio signal on the low bit rate for saving the channel communication usage for digital television broadcasting. The research ...

Robust Estimation Using Least Trimmed Squares

A robust procedure is proposed, starting from least trimmed squares as the initial estimator. The asymptotic distribution of the two-step and multi-step estimators is derived. This allows the use with a pre-specified efficiency under normality. It is argued that the good performance, together with the simplicity of the procedure, should make this the robust estimator of choice for applied work.

Least squares and maximum likelihood

Estimating Flow Length Distributions Using Least Square Method and Maximum Likelihood Estimation

Traffic sampling technology has been widely deployed in front of many high-speed network applications to alleviate the great pressure on packet capturing. However, knowing the number and length of the original flows is necessary for some applications. This paper provides a novel method that uses flow statistics formed from sampled packet stream to infer the absolute frequencies of lengths of fl...

Comparing between Maximum Likelihood and Least Square Estimators for Gompertz Software Reliability Model

Software reliability models (SRMs) are very important for estimating and predicting software reliability in the testing/debugging phase. The contributions of this paper are as follows. First, a historical review of the Gompertz SRM is given. Based on several software failure data, the parameters of the Gompertz software reliability model are estimated using two estimation methods, the tradition...