Interval fusion and selection procedures for regression with 
             functional inputs. Methods include a semiparametric approach based
             on Sliced Inverse Regression (SIR), as described in 
             <doi:10.1007/s11222-018-9806-6> (standard ridge and sparse SIR are 
             also included in the package) and a random forest based approach, 
             as described in <doi:10.1002/sam.11705>.

Implementation of the SSR-Algorithm. The Sign-Simplicity-Regression model is a nonparametric statistical model which is based on residual signs and simplicity assumptions on the regression function. Goal is to calculate the most parsimonious regression function satisfying the statistical adequacy requirements. Theory and functions are specified in Metzner (2020, ISBN: 979-8-68239-420-3, "Trendbasierte Prognostik") and Metzner (2021, ISBN: 979-8-59347-027-0, "Adäquates Maschinelles Lernen").

The Brazilian system for diploma registration and validation on technical and superior
    courses are managing by 'Sistec' platform, see <https://sistec.mec.gov.br/>. This package provides 
    tools for Brazilian institutions to update the student's registration and make data analysis 
    about their situation, retention and drop out.

This data package contains four datasets of quantitative PCR (qPCR)
  amplification curves that were used as supplementary data in the research
  article by Sisti et al. (2010), <doi:10.1186/1471-2105-11-186>.
  The primary dataset comprises a ten-fold dilution series spanning
  copy numbers from 3.14 × 10^7 to 3.14 × 10^2, with twelve replicates per
  concentration. These samples are based on a pGEM-T Promega plasmid containing
  a 104 bp fragment of the mitochondrial gene NADH dehydrogenase 1 (MT-ND1),
  amplified using the ND1/ND2 primer pair. The remaining three datasets contain
  qPCR results in the presence of specific PCR inhibitors: tannic acid,
  immunoglobulin G (IgG), and quercetin, respectively, to assess their effects
  on the amplification process. These datasets are useful for researchers 
  interested in PCR kinetics. The original raw data file is available as
  Additional File 1:
  <https://static-content.springer.com/esm/art%3A10.1186%2F1471-2105-11-186/MediaObjects/12859_2009_3643_MOESM1_ESM.XLS>.